{"cells":[{"cell_type":"markdown","metadata":{"trusted":true,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"D89B0EAB542642F98900CCC4D4E49360","runtime":{"status":"default","execution_status":null,"is_visible":false},"scrolled":false,"notebookId":"66cec22aeb486dd4e9a64332"},"source":"# baseline_高分辨率气候模式中台风轨迹检测  \n## 背景介绍  \n**热带气旋**是一种具有危害性的天气系统，常伴随狂风暴雨等极端天气。西北太平洋是全球热带气旋最活跃区域，我国是受台风影响最严重的国家之一。  \n\n\n![Image Name](https://cdn.kesci.com/upload/image/r4ir75rat1.png)  \n\n\n[**第六次国际耦合模式比较计划（CMIP6）** ](https://esgf-node.llnl.gov/projects/cmip6/) 提供了[**高分辨率模式比较计划（HighResMIP）**](https://pcmdi.llnl.gov/CMIP6/ArchiveStatistics/esgf_data_holdings/HighResMIP/index.html)，为分析热带气旋等提供了重要模拟数据，其中**热带气旋轨迹分布及强度变化**备受关注。热带气旋是一个**具有暖心结构的低压系统**，在北半球气流绕中心按逆时针方向旋转。越靠近热带气旋中心，气压越低，风力越大。本赛题需要建立合理的**约束条件或特征识别算法**，最终实现**西北太平洋海域（100°E-180°，0°N-60°N）逐6小时**的热带气旋路径检测，同时输出对应的**海平面最低气压和850hPa最大风速**。  \n\n\n![Image Name](https://cdn.kesci.com/upload/image/r4irf4uen4.jpg?imageView2/0/w/960/h/960)  \n"},{"cell_type":"markdown","metadata":{"id":"18711A7B69154907A27FA0930406B4F5","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"## 数据概述  \n赛题数据分为train和test两个文件夹，**区域为西北太平洋海域，时间分辨率为6小时，空间分辨率为0.5°**。  \n\ntrain文件夹包含以下5个文件：  \n① 2014年7月海平面气压模拟数据：psl_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc  \n② 2014年7月气温场模拟数据：ta_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc  \n③ 2014年7月经向风场模拟数据：ua_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc  \n④ 2014年7月纬向风场模拟数据：va_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc  \n⑤ 2014年7月检测所得的台风数据：train_tc_data.csv  \n\ntest文件夹包含以下9个文件：  \n① 2014年8月海平面气压模拟数据：psl_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201408010000-201408311800.nc  \n② 2014年9月海平面气压模拟数据：psl_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201409010000-201409301800.nc  \n③ 2014年8月气温场模拟数据：ta_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201408010000-201408311800.nc  \n④ 2014年9月气温场模拟数据：ta_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201409010000-201409301800.nc  \n⑤ 2014年8月经向风场模拟数据：ua_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201408010000-201408311800.nc  \n⑥ 2014年9月经向风场模拟数据：ua_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201409010000-201409301800.nc  \n⑦ 2014年8月纬向风场检测数据：va_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201408010000-201408311800.nc  \n⑧ 2014年9月纬向风场检测数据：va_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201409010000-201409301800.nc  \n⑨ 2014年8-9月有待检测的台风数据：test_tc_data_sample.csv  \n## 导入模块"},{"cell_type":"code","metadata":{"id":"A414F4F141A14A01B548F587F2F9AC89","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"import numpy as np\nimport pandas as pd\nimport xarray as xr\nimport cartopy.crs as ccrs\nimport cartopy.io.shapereader as shpreader\nimport cartopy.feature as cfeat\nimport cartopy.mpl.ticker as cmt\nfrom cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\nfrom cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER\nimport matplotlib.pyplot as plt\nimport metpy.calc as mpcalc\nfrom metpy.interpolate import cross_section\nfrom metpy.units import units\nimport cmaps\n\nimport warnings\nwarnings.filterwarnings('ignore')","outputs":[],"execution_count":1},{"cell_type":"markdown","metadata":{"id":"C5EFC5AD352E49A8A6183B15E598FE6B","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"## 读取热带气旋检测数据"},{"cell_type":"code","metadata":{"id":"810CF482643D4985AFA558B9F60AF78D","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true,"collapsed":false,"scrolled":false},"source":"# 读取2014年7月的西北太平洋热带气旋检测结果\ndf = pd.read_csv('/home/mw/input/typhoon/data/train/train_tc_data.csv')\ndf","outputs":[{"output_type":"execute_result","data":{"text/plain":"     number             time    lon   lat   pres  wind\n0         1    2014/7/1 0:00  113.0  19.5  98462    24\n1         1    2014/7/1 6:00  113.0  19.5  98470    26\n2         1   2014/7/1 12:00  113.0  19.5  98542    23\n3         1   2014/7/1 18:00  112.5  20.0  98605    22\n4         1    2014/7/2 0:00  112.5  19.5  98564    27\n..      ...              ...    ...   ...    ...   ...\n130       3   2014/7/26 6:00  115.5  26.0  98568    36\n131       3  2014/7/26 12:00  115.0  26.5  98890    36\n132       3  2014/7/26 18:00  113.5  27.0  99349    31\n133       3   2014/7/27 0:00  113.0  27.5  99698    32\n134       3   2014/7/27 6:00  112.5  28.5  99830    35\n\n[135 rows x 6 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>number</th>\n      <th>time</th>\n      <th>lon</th>\n      <th>lat</th>\n      <th>pres</th>\n      <th>wind</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>2014/7/1 0:00</td>\n      <td>113.0</td>\n      <td>19.5</td>\n      <td>98462</td>\n      <td>24</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>2014/7/1 6:00</td>\n      <td>113.0</td>\n      <td>19.5</td>\n      <td>98470</td>\n      <td>26</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>2014/7/1 12:00</td>\n      <td>113.0</td>\n      <td>19.5</td>\n      <td>98542</td>\n      <td>23</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1</td>\n      <td>2014/7/1 18:00</td>\n      <td>112.5</td>\n      <td>20.0</td>\n      <td>98605</td>\n      <td>22</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1</td>\n      <td>2014/7/2 0:00</td>\n      <td>112.5</td>\n      <td>19.5</td>\n      <td>98564</td>\n      <td>27</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>130</th>\n      <td>3</td>\n      <td>2014/7/26 6:00</td>\n      <td>115.5</td>\n      <td>26.0</td>\n      <td>98568</td>\n      <td>36</td>\n    </tr>\n    <tr>\n      <th>131</th>\n      <td>3</td>\n      <td>2014/7/26 12:00</td>\n      <td>115.0</td>\n      <td>26.5</td>\n      <td>98890</td>\n      <td>36</td>\n    </tr>\n    <tr>\n      <th>132</th>\n      <td>3</td>\n      <td>2014/7/26 18:00</td>\n      <td>113.5</td>\n      <td>27.0</td>\n      <td>99349</td>\n      <td>31</td>\n    </tr>\n    <tr>\n      <th>133</th>\n      <td>3</td>\n      <td>2014/7/27 0:00</td>\n      <td>113.0</td>\n      <td>27.5</td>\n      <td>99698</td>\n      <td>32</td>\n    </tr>\n    <tr>\n      <th>134</th>\n      <td>3</td>\n      <td>2014/7/27 6:00</td>\n      <td>112.5</td>\n      <td>28.5</td>\n      <td>99830</td>\n      <td>35</td>\n    </tr>\n  </tbody>\n</table>\n<p>135 rows × 6 columns</p>\n</div>"},"metadata":{},"execution_count":2}],"execution_count":2},{"cell_type":"markdown","metadata":{"id":"24153CE3528F49D399E81B2FEC02D432","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"上述检测结果包含3个热带气旋（**热带气旋编号是根据生成日期的先后顺序确定的**），其中包含每个热带气旋不同时刻的经纬度、最低海平面气压和850hPa最大风速  \n## 如何确定热带气旋轨迹点"},{"cell_type":"code","metadata":{"id":"C5924A71DB9042C18A2729A088F642F1","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 在训练数据中包含了热带气旋的轨迹和属性，后面展示如何从模拟数据中得到\ndf.iloc[119]","outputs":[{"output_type":"execute_result","data":{"text/plain":"number                  3\ntime      2014/7/23 12:00\nlon                 128.5\nlat                  22.0\npres                95505\nwind                   51\nName: 119, dtype: object"},"metadata":{},"execution_count":3}],"execution_count":3},{"cell_type":"markdown","metadata":{"id":"72FDA66F46304224A05F9BA8B882AFB5","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"### 气压"},{"cell_type":"code","metadata":{"id":"8DD904F4BC88472BB99C54A889346EA6","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 读取海平面气压\nds = xr.open_dataset('/home/mw/input/typhoon/data/train/psl_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc')\npsl = ds.psl\npsl","outputs":[{"output_type":"execute_result","data":{"text/plain":"<xarray.DataArray 'psl' (time: 124, lat: 121, lon: 161)> Size: 10MB\n[2415644 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:  air_pressure_at_sea_level\n    long_name:      Sea Level Pressure\n    comment:        Sea Level Pressure\n    units:          Pa\n    original_name:  msl\n    cell_methods:   area: mean time: point\n    cell_measures:  area: areacella\n    history:        2017-09-01T06:16:29Z altered by CMOR: replaced missing va...","text/html":"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n<defs>\n<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 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10px;\n}\n\n.xr-var-name:hover,\n.xr-var-dims:hover,\n.xr-var-dtype:hover,\n.xr-attrs dt:hover {\n  overflow: visible;\n  width: auto;\n  z-index: 1;\n}\n\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  display: none;\n  background-color: var(--xr-background-color) !important;\n  padding-bottom: 5px !important;\n}\n\n.xr-var-attrs-in:checked ~ .xr-var-attrs,\n.xr-var-data-in:checked ~ .xr-var-data,\n.xr-index-data-in:checked ~ .xr-index-data {\n  display: block;\n}\n\n.xr-var-data > table {\n  float: right;\n}\n\n.xr-var-name span,\n.xr-var-data,\n.xr-index-name div,\n.xr-index-data,\n.xr-attrs {\n  padding-left: 25px !important;\n}\n\n.xr-attrs,\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  grid-column: 1 / -1;\n}\n\ndl.xr-attrs {\n  padding: 0;\n  margin: 0;\n  display: grid;\n  grid-template-columns: 125px auto;\n}\n\n.xr-attrs dt,\n.xr-attrs dd {\n  padding: 0;\n  margin: 0;\n  float: left;\n  padding-right: 10px;\n  width: auto;\n}\n\n.xr-attrs dt {\n  font-weight: normal;\n  grid-column: 1;\n}\n\n.xr-attrs dt:hover span {\n  display: inline-block;\n  background: var(--xr-background-color);\n  padding-right: 10px;\n}\n\n.xr-attrs dd {\n  grid-column: 2;\n  white-space: pre-wrap;\n  word-break: break-all;\n}\n\n.xr-icon-database,\n.xr-icon-file-text2,\n.xr-no-icon {\n  display: inline-block;\n  vertical-align: middle;\n  width: 1em;\n  height: 1.5em !important;\n  stroke-width: 0;\n  stroke: currentColor;\n  fill: currentColor;\n}\n</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;psl&#x27; (time: 124, lat: 121, lon: 161)&gt; Size: 10MB\n[2415644 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:  air_pressure_at_sea_level\n    long_name:      Sea Level Pressure\n    comment:        Sea Level Pressure\n    units:          Pa\n    original_name:  msl\n    cell_methods:   area: mean time: point\n    cell_measures:  area: areacella\n    history:        2017-09-01T06:16:29Z altered by CMOR: replaced missing va...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'psl'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 124</li><li><span class='xr-has-index'>lat</span>: 121</li><li><span class='xr-has-index'>lon</span>: 161</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7ee27a77-ff41-4ebe-bed2-ef515d890a4c' class='xr-array-in' type='checkbox' checked><label for='section-7ee27a77-ff41-4ebe-bed2-ef515d890a4c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[2415644 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-7bcf9161-2654-4d91-9e14-32bd473882e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7bcf9161-2654-4d91-9e14-32bd473882e2' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2014-07-01 ... 2014-07-31T18:00:00</div><input id='attrs-bb7c1bde-a7ea-4c8b-a638-47c7d0a65ba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb7c1bde-a7ea-4c8b-a638-47c7d0a65ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc69be80-7e82-4b7f-90f9-a12e7cfee0d8' class='xr-var-data-in' type='checkbox'><label for='data-bc69be80-7e82-4b7f-90f9-a12e7cfee0d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2014-07-01T00:00:00.000000000&#x27;, &#x27;2014-07-01T06:00:00.000000000&#x27;,\n       &#x27;2014-07-01T12:00:00.000000000&#x27;, &#x27;2014-07-01T18:00:00.000000000&#x27;,\n       &#x27;2014-07-02T00:00:00.000000000&#x27;, &#x27;2014-07-02T06:00:00.000000000&#x27;,\n       &#x27;2014-07-02T12:00:00.000000000&#x27;, &#x27;2014-07-02T18:00:00.000000000&#x27;,\n       &#x27;2014-07-03T00:00:00.000000000&#x27;, &#x27;2014-07-03T06:00:00.000000000&#x27;,\n       &#x27;2014-07-03T12:00:00.000000000&#x27;, &#x27;2014-07-03T18:00:00.000000000&#x27;,\n       &#x27;2014-07-04T00:00:00.000000000&#x27;, &#x27;2014-07-04T06:00:00.000000000&#x27;,\n       &#x27;2014-07-04T12:00:00.000000000&#x27;, &#x27;2014-07-04T18:00:00.000000000&#x27;,\n       &#x27;2014-07-05T00:00:00.000000000&#x27;, &#x27;2014-07-05T06:00:00.000000000&#x27;,\n       &#x27;2014-07-05T12:00:00.000000000&#x27;, &#x27;2014-07-05T18:00:00.000000000&#x27;,\n       &#x27;2014-07-06T00:00:00.000000000&#x27;, &#x27;2014-07-06T06:00:00.000000000&#x27;,\n       &#x27;2014-07-06T12:00:00.000000000&#x27;, &#x27;2014-07-06T18:00:00.000000000&#x27;,\n       &#x27;2014-07-07T00:00:00.000000000&#x27;, &#x27;2014-07-07T06:00:00.000000000&#x27;,\n       &#x27;2014-07-07T12:00:00.000000000&#x27;, &#x27;2014-07-07T18:00:00.000000000&#x27;,\n       &#x27;2014-07-08T00:00:00.000000000&#x27;, &#x27;2014-07-08T06:00:00.000000000&#x27;,\n       &#x27;2014-07-08T12:00:00.000000000&#x27;, &#x27;2014-07-08T18:00:00.000000000&#x27;,\n       &#x27;2014-07-09T00:00:00.000000000&#x27;, &#x27;2014-07-09T06:00:00.000000000&#x27;,\n       &#x27;2014-07-09T12:00:00.000000000&#x27;, &#x27;2014-07-09T18:00:00.000000000&#x27;,\n       &#x27;2014-07-10T00:00:00.000000000&#x27;, &#x27;2014-07-10T06:00:00.000000000&#x27;,\n       &#x27;2014-07-10T12:00:00.000000000&#x27;, &#x27;2014-07-10T18:00:00.000000000&#x27;,\n       &#x27;2014-07-11T00:00:00.000000000&#x27;, &#x27;2014-07-11T06:00:00.000000000&#x27;,\n       &#x27;2014-07-11T12:00:00.000000000&#x27;, &#x27;2014-07-11T18:00:00.000000000&#x27;,\n       &#x27;2014-07-12T00:00:00.000000000&#x27;, &#x27;2014-07-12T06:00:00.000000000&#x27;,\n       &#x27;2014-07-12T12:00:00.000000000&#x27;, &#x27;2014-07-12T18:00:00.000000000&#x27;,\n       &#x27;2014-07-13T00:00:00.000000000&#x27;, &#x27;2014-07-13T06:00:00.000000000&#x27;,\n       &#x27;2014-07-13T12:00:00.000000000&#x27;, &#x27;2014-07-13T18:00:00.000000000&#x27;,\n       &#x27;2014-07-14T00:00:00.000000000&#x27;, &#x27;2014-07-14T06:00:00.000000000&#x27;,\n       &#x27;2014-07-14T12:00:00.000000000&#x27;, &#x27;2014-07-14T18:00:00.000000000&#x27;,\n       &#x27;2014-07-15T00:00:00.000000000&#x27;, &#x27;2014-07-15T06:00:00.000000000&#x27;,\n       &#x27;2014-07-15T12:00:00.000000000&#x27;, &#x27;2014-07-15T18:00:00.000000000&#x27;,\n       &#x27;2014-07-16T00:00:00.000000000&#x27;, &#x27;2014-07-16T06:00:00.000000000&#x27;,\n       &#x27;2014-07-16T12:00:00.000000000&#x27;, &#x27;2014-07-16T18:00:00.000000000&#x27;,\n       &#x27;2014-07-17T00:00:00.000000000&#x27;, &#x27;2014-07-17T06:00:00.000000000&#x27;,\n       &#x27;2014-07-17T12:00:00.000000000&#x27;, &#x27;2014-07-17T18:00:00.000000000&#x27;,\n       &#x27;2014-07-18T00:00:00.000000000&#x27;, &#x27;2014-07-18T06:00:00.000000000&#x27;,\n       &#x27;2014-07-18T12:00:00.000000000&#x27;, &#x27;2014-07-18T18:00:00.000000000&#x27;,\n       &#x27;2014-07-19T00:00:00.000000000&#x27;, &#x27;2014-07-19T06:00:00.000000000&#x27;,\n       &#x27;2014-07-19T12:00:00.000000000&#x27;, &#x27;2014-07-19T18:00:00.000000000&#x27;,\n       &#x27;2014-07-20T00:00:00.000000000&#x27;, &#x27;2014-07-20T06:00:00.000000000&#x27;,\n       &#x27;2014-07-20T12:00:00.000000000&#x27;, &#x27;2014-07-20T18:00:00.000000000&#x27;,\n       &#x27;2014-07-21T00:00:00.000000000&#x27;, &#x27;2014-07-21T06:00:00.000000000&#x27;,\n       &#x27;2014-07-21T12:00:00.000000000&#x27;, &#x27;2014-07-21T18:00:00.000000000&#x27;,\n       &#x27;2014-07-22T00:00:00.000000000&#x27;, &#x27;2014-07-22T06:00:00.000000000&#x27;,\n       &#x27;2014-07-22T12:00:00.000000000&#x27;, &#x27;2014-07-22T18:00:00.000000000&#x27;,\n       &#x27;2014-07-23T00:00:00.000000000&#x27;, &#x27;2014-07-23T06:00:00.000000000&#x27;,\n       &#x27;2014-07-23T12:00:00.000000000&#x27;, &#x27;2014-07-23T18:00:00.000000000&#x27;,\n       &#x27;2014-07-24T00:00:00.000000000&#x27;, &#x27;2014-07-24T06:00:00.000000000&#x27;,\n       &#x27;2014-07-24T12:00:00.000000000&#x27;, &#x27;2014-07-24T18:00:00.000000000&#x27;,\n       &#x27;2014-07-25T00:00:00.000000000&#x27;, &#x27;2014-07-25T06:00:00.000000000&#x27;,\n       &#x27;2014-07-25T12:00:00.000000000&#x27;, &#x27;2014-07-25T18:00:00.000000000&#x27;,\n       &#x27;2014-07-26T00:00:00.000000000&#x27;, &#x27;2014-07-26T06:00:00.000000000&#x27;,\n       &#x27;2014-07-26T12:00:00.000000000&#x27;, &#x27;2014-07-26T18:00:00.000000000&#x27;,\n       &#x27;2014-07-27T00:00:00.000000000&#x27;, &#x27;2014-07-27T06:00:00.000000000&#x27;,\n       &#x27;2014-07-27T12:00:00.000000000&#x27;, &#x27;2014-07-27T18:00:00.000000000&#x27;,\n       &#x27;2014-07-28T00:00:00.000000000&#x27;, &#x27;2014-07-28T06:00:00.000000000&#x27;,\n       &#x27;2014-07-28T12:00:00.000000000&#x27;, &#x27;2014-07-28T18:00:00.000000000&#x27;,\n       &#x27;2014-07-29T00:00:00.000000000&#x27;, &#x27;2014-07-29T06:00:00.000000000&#x27;,\n       &#x27;2014-07-29T12:00:00.000000000&#x27;, &#x27;2014-07-29T18:00:00.000000000&#x27;,\n       &#x27;2014-07-30T00:00:00.000000000&#x27;, &#x27;2014-07-30T06:00:00.000000000&#x27;,\n       &#x27;2014-07-30T12:00:00.000000000&#x27;, &#x27;2014-07-30T18:00:00.000000000&#x27;,\n       &#x27;2014-07-31T00:00:00.000000000&#x27;, &#x27;2014-07-31T06:00:00.000000000&#x27;,\n       &#x27;2014-07-31T12:00:00.000000000&#x27;, &#x27;2014-07-31T18:00:00.000000000&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.5 1.0 1.5 ... 59.0 59.5 60.0</div><input id='attrs-edd6b296-15a5-4e44-9b31-d469f6e79710' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edd6b296-15a5-4e44-9b31-d469f6e79710' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-032f6f2c-0bac-44ab-bd6f-d212af30960f' class='xr-var-data-in' type='checkbox'><label for='data-032f6f2c-0bac-44ab-bd6f-d212af30960f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,\n        6. ,  6.5,  7. ,  7.5,  8. ,  8.5,  9. ,  9.5, 10. , 10.5, 11. , 11.5,\n       12. , 12.5, 13. , 13.5, 14. , 14.5, 15. , 15.5, 16. , 16.5, 17. , 17.5,\n       18. , 18.5, 19. , 19.5, 20. , 20.5, 21. , 21.5, 22. , 22.5, 23. , 23.5,\n       24. , 24.5, 25. , 25.5, 26. , 26.5, 27. , 27.5, 28. , 28.5, 29. , 29.5,\n       30. , 30.5, 31. , 31.5, 32. , 32.5, 33. , 33.5, 34. , 34.5, 35. , 35.5,\n       36. , 36.5, 37. , 37.5, 38. , 38.5, 39. , 39.5, 40. , 40.5, 41. , 41.5,\n       42. , 42.5, 43. , 43.5, 44. , 44.5, 45. , 45.5, 46. , 46.5, 47. , 47.5,\n       48. , 48.5, 49. , 49.5, 50. , 50.5, 51. , 51.5, 52. , 52.5, 53. , 53.5,\n       54. , 54.5, 55. , 55.5, 56. , 56.5, 57. , 57.5, 58. , 58.5, 59. , 59.5,\n       60. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.5 101.0 ... 179.5 180.0</div><input id='attrs-9cc66953-3dd1-4318-adaa-d008e8fdceea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cc66953-3dd1-4318-adaa-d008e8fdceea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4649618-aebf-4920-9e24-0d749b354c0b' class='xr-var-data-in' type='checkbox'><label for='data-f4649618-aebf-4920-9e24-0d749b354c0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.5, 101. , 101.5, 102. , 102.5, 103. , 103.5, 104. , 104.5,\n       105. , 105.5, 106. , 106.5, 107. , 107.5, 108. , 108.5, 109. , 109.5,\n       110. , 110.5, 111. , 111.5, 112. , 112.5, 113. , 113.5, 114. , 114.5,\n       115. , 115.5, 116. , 116.5, 117. , 117.5, 118. , 118.5, 119. , 119.5,\n       120. , 120.5, 121. , 121.5, 122. , 122.5, 123. , 123.5, 124. , 124.5,\n       125. , 125.5, 126. , 126.5, 127. , 127.5, 128. , 128.5, 129. , 129.5,\n       130. , 130.5, 131. , 131.5, 132. , 132.5, 133. , 133.5, 134. , 134.5,\n       135. , 135.5, 136. , 136.5, 137. , 137.5, 138. , 138.5, 139. , 139.5,\n       140. , 140.5, 141. , 141.5, 142. , 142.5, 143. , 143.5, 144. , 144.5,\n       145. , 145.5, 146. , 146.5, 147. , 147.5, 148. , 148.5, 149. , 149.5,\n       150. , 150.5, 151. , 151.5, 152. , 152.5, 153. , 153.5, 154. , 154.5,\n       155. , 155.5, 156. , 156.5, 157. , 157.5, 158. , 158.5, 159. , 159.5,\n       160. , 160.5, 161. , 161.5, 162. , 162.5, 163. , 163.5, 164. , 164.5,\n       165. , 165.5, 166. , 166.5, 167. , 167.5, 168. , 168.5, 169. , 169.5,\n       170. , 170.5, 171. , 171.5, 172. , 172.5, 173. , 173.5, 174. , 174.5,\n       175. , 175.5, 176. , 176.5, 177. , 177.5, 178. , 178.5, 179. , 179.5,\n       180. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-05b4b63e-e168-48b9-abe9-95e95b15ce90' class='xr-section-summary-in' type='checkbox'  ><label for='section-05b4b63e-e168-48b9-abe9-95e95b15ce90' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8ba0d913-b711-422d-8b61-35fa3a9288b3' class='xr-index-data-in' type='checkbox'/><label for='index-8ba0d913-b711-422d-8b61-35fa3a9288b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2014-07-01 00:00:00&#x27;, &#x27;2014-07-01 06:00:00&#x27;,\n               &#x27;2014-07-01 12:00:00&#x27;, &#x27;2014-07-01 18:00:00&#x27;,\n               &#x27;2014-07-02 00:00:00&#x27;, &#x27;2014-07-02 06:00:00&#x27;,\n               &#x27;2014-07-02 12:00:00&#x27;, &#x27;2014-07-02 18:00:00&#x27;,\n               &#x27;2014-07-03 00:00:00&#x27;, &#x27;2014-07-03 06:00:00&#x27;,\n               ...\n               &#x27;2014-07-29 12:00:00&#x27;, &#x27;2014-07-29 18:00:00&#x27;,\n               &#x27;2014-07-30 00:00:00&#x27;, &#x27;2014-07-30 06:00:00&#x27;,\n               &#x27;2014-07-30 12:00:00&#x27;, &#x27;2014-07-30 18:00:00&#x27;,\n               &#x27;2014-07-31 00:00:00&#x27;, &#x27;2014-07-31 06:00:00&#x27;,\n               &#x27;2014-07-31 12:00:00&#x27;, &#x27;2014-07-31 18:00:00&#x27;],\n              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=124, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-577fe589-2e87-4792-b5ec-805313e4fcbb' class='xr-index-data-in' type='checkbox'/><label for='index-577fe589-2e87-4792-b5ec-805313e4fcbb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0,  0.5,  1.0,  1.5,  2.0,  2.5,  3.0,  3.5,  4.0,  4.5,\n       ...\n       55.5, 56.0, 56.5, 57.0, 57.5, 58.0, 58.5, 59.0, 59.5, 60.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dac3c603-4a8e-4b0c-a5fb-146bb6250588' class='xr-index-data-in' type='checkbox'/><label for='index-dac3c603-4a8e-4b0c-a5fb-146bb6250588' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100.0, 100.5, 101.0, 101.5, 102.0, 102.5, 103.0, 103.5, 104.0, 104.5,\n       ...\n       175.5, 176.0, 176.5, 177.0, 177.5, 178.0, 178.5, 179.0, 179.5, 180.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=161))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8b6baf6-aa53-4e75-9a19-e4557d442489' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f8b6baf6-aa53-4e75-9a19-e4557d442489' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_pressure_at_sea_level</dd><dt><span>long_name :</span></dt><dd>Sea Level Pressure</dd><dt><span>comment :</span></dt><dd>Sea Level Pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>original_name :</span></dt><dd>msl</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2017-09-01T06:16:29Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20). 2017-09-01T06:16:29Z altered by CMOR: Inverted axis: lat.</dd></dl></div></li></ul></div></div>"},"metadata":{},"execution_count":4}],"execution_count":4},{"cell_type":"code","metadata":{"id":"D2E1FA6691D34A03A55270C33F88AD34","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 获取经纬度数据\nlon = ds.lon\nlat = ds.lat","outputs":[],"execution_count":5},{"cell_type":"code","metadata":{"id":"995790A41D14423E96AF2B7EACDC27CA","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 50],crs=ccrs.PlateCarree())\nplt.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels=False                               \ngl.right_labels=False\n\nim = ax.contourf(lon, lat, psl.sel(time='2014-7-23 12:00'), \n                 np.arange(95000,105000,100),\n                 cmap=cmaps.cmp_b2r, \n                 transform=ccrs.PlateCarree())\n\ncb = fig.colorbar(im, orientation='vertical', \n                  extend='both', shrink=0.6,\n                  fraction=0.03, pad=0.02) \ncb.set_label(label='Pressure (Pa)', size=15)\ncb.ax.tick_params(labelsize=15)\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('Surface',loc='left',fontsize=15)\nplt.title(str(psl.sel(time='2014-7-23 12:00').time.values)[0:16],loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/995790A41D14423E96AF2B7EACDC27CA/six1c9zf3p.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":6},{"cell_type":"code","metadata":{"id":"9CF272C4893B4523941167F76363C258","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 与训练集中的气压完全一致\npsl.sel(time='2014-7-23 12:00',lon=128.5,lat=22.0).values","outputs":[{"output_type":"execute_result","data":{"text/plain":"array(95505.25, dtype=float32)"},"metadata":{},"execution_count":7}],"execution_count":7},{"cell_type":"markdown","metadata":{"id":"6BB86F4A180D4E2EA55387E41E9673B5","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"### 温度"},{"cell_type":"code","metadata":{"id":"F9DE6E6B747A41C19E9B7FAF94FBF2CC","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 读取温度\nds = xr.open_dataset('/home/mw/input/typhoon/data/train/ta_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc')\nta = ds.ta\nta","outputs":[{"output_type":"execute_result","data":{"text/plain":"<xarray.DataArray 'ta' (time: 124, plev: 7, lat: 121, lon: 161)> Size: 68MB\n[16909508 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:  air_temperature\n    long_name:      Air 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!important;\n}\n\n.xr-var-attrs-in:checked ~ .xr-var-attrs,\n.xr-var-data-in:checked ~ .xr-var-data,\n.xr-index-data-in:checked ~ .xr-index-data {\n  display: block;\n}\n\n.xr-var-data > table {\n  float: right;\n}\n\n.xr-var-name span,\n.xr-var-data,\n.xr-index-name div,\n.xr-index-data,\n.xr-attrs {\n  padding-left: 25px !important;\n}\n\n.xr-attrs,\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  grid-column: 1 / -1;\n}\n\ndl.xr-attrs {\n  padding: 0;\n  margin: 0;\n  display: grid;\n  grid-template-columns: 125px auto;\n}\n\n.xr-attrs dt,\n.xr-attrs dd {\n  padding: 0;\n  margin: 0;\n  float: left;\n  padding-right: 10px;\n  width: auto;\n}\n\n.xr-attrs dt {\n  font-weight: normal;\n  grid-column: 1;\n}\n\n.xr-attrs dt:hover span {\n  display: inline-block;\n  background: var(--xr-background-color);\n  padding-right: 10px;\n}\n\n.xr-attrs dd {\n  grid-column: 2;\n  white-space: pre-wrap;\n  word-break: break-all;\n}\n\n.xr-icon-database,\n.xr-icon-file-text2,\n.xr-no-icon {\n  display: inline-block;\n  vertical-align: middle;\n  width: 1em;\n  height: 1.5em !important;\n  stroke-width: 0;\n  stroke: currentColor;\n  fill: currentColor;\n}\n</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;ta&#x27; (time: 124, plev: 7, lat: 121, lon: 161)&gt; Size: 68MB\n[16909508 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:  air_temperature\n    long_name:      Air Temperature\n    comment:        Air Temperature\n    units:          K\n    original_name:  t\n    cell_methods:   area: mean time: point\n    cell_measures:  area: areacella\n    history:        2017-09-01T06:33:19Z altered by CMOR: replaced missing va...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ta'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 124</li><li><span class='xr-has-index'>plev</span>: 7</li><li><span class='xr-has-index'>lat</span>: 121</li><li><span class='xr-has-index'>lon</span>: 161</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-23f1c618-1508-40da-b6d3-42644be3e4f3' class='xr-array-in' type='checkbox' checked><label for='section-23f1c618-1508-40da-b6d3-42644be3e4f3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[16909508 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-b9f14604-5c53-4df6-956d-aca53ec80a30' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b9f14604-5c53-4df6-956d-aca53ec80a30' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2014-07-01 ... 2014-07-31T18:00:00</div><input id='attrs-291843ae-e809-43b7-9a24-75a9dcb7602d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-291843ae-e809-43b7-9a24-75a9dcb7602d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37c9be88-81c7-42fc-bda6-86f3823f3745' class='xr-var-data-in' type='checkbox'><label for='data-37c9be88-81c7-42fc-bda6-86f3823f3745' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2014-07-01T00:00:00.000000000&#x27;, &#x27;2014-07-01T06:00:00.000000000&#x27;,\n       &#x27;2014-07-01T12:00:00.000000000&#x27;, &#x27;2014-07-01T18:00:00.000000000&#x27;,\n       &#x27;2014-07-02T00:00:00.000000000&#x27;, &#x27;2014-07-02T06:00:00.000000000&#x27;,\n       &#x27;2014-07-02T12:00:00.000000000&#x27;, &#x27;2014-07-02T18:00:00.000000000&#x27;,\n       &#x27;2014-07-03T00:00:00.000000000&#x27;, &#x27;2014-07-03T06:00:00.000000000&#x27;,\n       &#x27;2014-07-03T12:00:00.000000000&#x27;, &#x27;2014-07-03T18:00:00.000000000&#x27;,\n       &#x27;2014-07-04T00:00:00.000000000&#x27;, &#x27;2014-07-04T06:00:00.000000000&#x27;,\n       &#x27;2014-07-04T12:00:00.000000000&#x27;, &#x27;2014-07-04T18:00:00.000000000&#x27;,\n       &#x27;2014-07-05T00:00:00.000000000&#x27;, &#x27;2014-07-05T06:00:00.000000000&#x27;,\n       &#x27;2014-07-05T12:00:00.000000000&#x27;, &#x27;2014-07-05T18:00:00.000000000&#x27;,\n       &#x27;2014-07-06T00:00:00.000000000&#x27;, &#x27;2014-07-06T06:00:00.000000000&#x27;,\n       &#x27;2014-07-06T12:00:00.000000000&#x27;, &#x27;2014-07-06T18:00:00.000000000&#x27;,\n       &#x27;2014-07-07T00:00:00.000000000&#x27;, &#x27;2014-07-07T06:00:00.000000000&#x27;,\n       &#x27;2014-07-07T12:00:00.000000000&#x27;, &#x27;2014-07-07T18:00:00.000000000&#x27;,\n       &#x27;2014-07-08T00:00:00.000000000&#x27;, &#x27;2014-07-08T06:00:00.000000000&#x27;,\n       &#x27;2014-07-08T12:00:00.000000000&#x27;, &#x27;2014-07-08T18:00:00.000000000&#x27;,\n       &#x27;2014-07-09T00:00:00.000000000&#x27;, &#x27;2014-07-09T06:00:00.000000000&#x27;,\n       &#x27;2014-07-09T12:00:00.000000000&#x27;, &#x27;2014-07-09T18:00:00.000000000&#x27;,\n       &#x27;2014-07-10T00:00:00.000000000&#x27;, &#x27;2014-07-10T06:00:00.000000000&#x27;,\n       &#x27;2014-07-10T12:00:00.000000000&#x27;, &#x27;2014-07-10T18:00:00.000000000&#x27;,\n       &#x27;2014-07-11T00:00:00.000000000&#x27;, &#x27;2014-07-11T06:00:00.000000000&#x27;,\n       &#x27;2014-07-11T12:00:00.000000000&#x27;, &#x27;2014-07-11T18:00:00.000000000&#x27;,\n       &#x27;2014-07-12T00:00:00.000000000&#x27;, &#x27;2014-07-12T06:00:00.000000000&#x27;,\n       &#x27;2014-07-12T12:00:00.000000000&#x27;, &#x27;2014-07-12T18:00:00.000000000&#x27;,\n       &#x27;2014-07-13T00:00:00.000000000&#x27;, &#x27;2014-07-13T06:00:00.000000000&#x27;,\n       &#x27;2014-07-13T12:00:00.000000000&#x27;, &#x27;2014-07-13T18:00:00.000000000&#x27;,\n       &#x27;2014-07-14T00:00:00.000000000&#x27;, &#x27;2014-07-14T06:00:00.000000000&#x27;,\n       &#x27;2014-07-14T12:00:00.000000000&#x27;, &#x27;2014-07-14T18:00:00.000000000&#x27;,\n       &#x27;2014-07-15T00:00:00.000000000&#x27;, &#x27;2014-07-15T06:00:00.000000000&#x27;,\n       &#x27;2014-07-15T12:00:00.000000000&#x27;, &#x27;2014-07-15T18:00:00.000000000&#x27;,\n       &#x27;2014-07-16T00:00:00.000000000&#x27;, &#x27;2014-07-16T06:00:00.000000000&#x27;,\n       &#x27;2014-07-16T12:00:00.000000000&#x27;, &#x27;2014-07-16T18:00:00.000000000&#x27;,\n       &#x27;2014-07-17T00:00:00.000000000&#x27;, &#x27;2014-07-17T06:00:00.000000000&#x27;,\n       &#x27;2014-07-17T12:00:00.000000000&#x27;, &#x27;2014-07-17T18:00:00.000000000&#x27;,\n       &#x27;2014-07-18T00:00:00.000000000&#x27;, &#x27;2014-07-18T06:00:00.000000000&#x27;,\n       &#x27;2014-07-18T12:00:00.000000000&#x27;, &#x27;2014-07-18T18:00:00.000000000&#x27;,\n       &#x27;2014-07-19T00:00:00.000000000&#x27;, &#x27;2014-07-19T06:00:00.000000000&#x27;,\n       &#x27;2014-07-19T12:00:00.000000000&#x27;, &#x27;2014-07-19T18:00:00.000000000&#x27;,\n       &#x27;2014-07-20T00:00:00.000000000&#x27;, &#x27;2014-07-20T06:00:00.000000000&#x27;,\n       &#x27;2014-07-20T12:00:00.000000000&#x27;, &#x27;2014-07-20T18:00:00.000000000&#x27;,\n       &#x27;2014-07-21T00:00:00.000000000&#x27;, &#x27;2014-07-21T06:00:00.000000000&#x27;,\n       &#x27;2014-07-21T12:00:00.000000000&#x27;, &#x27;2014-07-21T18:00:00.000000000&#x27;,\n       &#x27;2014-07-22T00:00:00.000000000&#x27;, &#x27;2014-07-22T06:00:00.000000000&#x27;,\n       &#x27;2014-07-22T12:00:00.000000000&#x27;, &#x27;2014-07-22T18:00:00.000000000&#x27;,\n       &#x27;2014-07-23T00:00:00.000000000&#x27;, &#x27;2014-07-23T06:00:00.000000000&#x27;,\n       &#x27;2014-07-23T12:00:00.000000000&#x27;, &#x27;2014-07-23T18:00:00.000000000&#x27;,\n       &#x27;2014-07-24T00:00:00.000000000&#x27;, &#x27;2014-07-24T06:00:00.000000000&#x27;,\n       &#x27;2014-07-24T12:00:00.000000000&#x27;, &#x27;2014-07-24T18:00:00.000000000&#x27;,\n       &#x27;2014-07-25T00:00:00.000000000&#x27;, &#x27;2014-07-25T06:00:00.000000000&#x27;,\n       &#x27;2014-07-25T12:00:00.000000000&#x27;, &#x27;2014-07-25T18:00:00.000000000&#x27;,\n       &#x27;2014-07-26T00:00:00.000000000&#x27;, &#x27;2014-07-26T06:00:00.000000000&#x27;,\n       &#x27;2014-07-26T12:00:00.000000000&#x27;, &#x27;2014-07-26T18:00:00.000000000&#x27;,\n       &#x27;2014-07-27T00:00:00.000000000&#x27;, &#x27;2014-07-27T06:00:00.000000000&#x27;,\n       &#x27;2014-07-27T12:00:00.000000000&#x27;, &#x27;2014-07-27T18:00:00.000000000&#x27;,\n       &#x27;2014-07-28T00:00:00.000000000&#x27;, &#x27;2014-07-28T06:00:00.000000000&#x27;,\n       &#x27;2014-07-28T12:00:00.000000000&#x27;, &#x27;2014-07-28T18:00:00.000000000&#x27;,\n       &#x27;2014-07-29T00:00:00.000000000&#x27;, &#x27;2014-07-29T06:00:00.000000000&#x27;,\n       &#x27;2014-07-29T12:00:00.000000000&#x27;, &#x27;2014-07-29T18:00:00.000000000&#x27;,\n       &#x27;2014-07-30T00:00:00.000000000&#x27;, &#x27;2014-07-30T06:00:00.000000000&#x27;,\n       &#x27;2014-07-30T12:00:00.000000000&#x27;, &#x27;2014-07-30T18:00:00.000000000&#x27;,\n       &#x27;2014-07-31T00:00:00.000000000&#x27;, &#x27;2014-07-31T06:00:00.000000000&#x27;,\n       &#x27;2014-07-31T12:00:00.000000000&#x27;, &#x27;2014-07-31T18:00:00.000000000&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.25e+04 8.5e+04 ... 2.5e+04 5e+03</div><input id='attrs-bde88fe1-2e12-4fca-a576-4416805473de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bde88fe1-2e12-4fca-a576-4416805473de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cf3e576-830b-469b-a05a-6f8757799eb5' class='xr-var-data-in' type='checkbox'><label for='data-7cf3e576-830b-469b-a05a-6f8757799eb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([92500., 85000., 70000., 60000., 50000., 25000.,  5000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.5 1.0 1.5 ... 59.0 59.5 60.0</div><input id='attrs-2cf1412e-7673-4eab-afb0-26d0d7f69cad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cf1412e-7673-4eab-afb0-26d0d7f69cad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b738fb9-7743-4dd0-b0a0-41e526f5dc99' class='xr-var-data-in' type='checkbox'><label for='data-6b738fb9-7743-4dd0-b0a0-41e526f5dc99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,\n        6. ,  6.5,  7. ,  7.5,  8. ,  8.5,  9. ,  9.5, 10. , 10.5, 11. , 11.5,\n       12. , 12.5, 13. , 13.5, 14. , 14.5, 15. , 15.5, 16. , 16.5, 17. , 17.5,\n       18. , 18.5, 19. , 19.5, 20. , 20.5, 21. , 21.5, 22. , 22.5, 23. , 23.5,\n       24. , 24.5, 25. , 25.5, 26. , 26.5, 27. , 27.5, 28. , 28.5, 29. , 29.5,\n       30. , 30.5, 31. , 31.5, 32. , 32.5, 33. , 33.5, 34. , 34.5, 35. , 35.5,\n       36. , 36.5, 37. , 37.5, 38. , 38.5, 39. , 39.5, 40. , 40.5, 41. , 41.5,\n       42. , 42.5, 43. , 43.5, 44. , 44.5, 45. , 45.5, 46. , 46.5, 47. , 47.5,\n       48. , 48.5, 49. , 49.5, 50. , 50.5, 51. , 51.5, 52. , 52.5, 53. , 53.5,\n       54. , 54.5, 55. , 55.5, 56. , 56.5, 57. , 57.5, 58. , 58.5, 59. , 59.5,\n       60. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.5 101.0 ... 179.5 180.0</div><input id='attrs-2d5f4272-723a-4a55-8582-d4d111f66118' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d5f4272-723a-4a55-8582-d4d111f66118' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-764e2720-d9b9-4ee6-a988-05ee70170d86' class='xr-var-data-in' type='checkbox'><label for='data-764e2720-d9b9-4ee6-a988-05ee70170d86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.5, 101. , 101.5, 102. , 102.5, 103. , 103.5, 104. , 104.5,\n       105. , 105.5, 106. , 106.5, 107. , 107.5, 108. , 108.5, 109. , 109.5,\n       110. , 110.5, 111. , 111.5, 112. , 112.5, 113. , 113.5, 114. , 114.5,\n       115. , 115.5, 116. , 116.5, 117. , 117.5, 118. , 118.5, 119. , 119.5,\n       120. , 120.5, 121. , 121.5, 122. , 122.5, 123. , 123.5, 124. , 124.5,\n       125. , 125.5, 126. , 126.5, 127. , 127.5, 128. , 128.5, 129. , 129.5,\n       130. , 130.5, 131. , 131.5, 132. , 132.5, 133. , 133.5, 134. , 134.5,\n       135. , 135.5, 136. , 136.5, 137. , 137.5, 138. , 138.5, 139. , 139.5,\n       140. , 140.5, 141. , 141.5, 142. , 142.5, 143. , 143.5, 144. , 144.5,\n       145. , 145.5, 146. , 146.5, 147. , 147.5, 148. , 148.5, 149. , 149.5,\n       150. , 150.5, 151. , 151.5, 152. , 152.5, 153. , 153.5, 154. , 154.5,\n       155. , 155.5, 156. , 156.5, 157. , 157.5, 158. , 158.5, 159. , 159.5,\n       160. , 160.5, 161. , 161.5, 162. , 162.5, 163. , 163.5, 164. , 164.5,\n       165. , 165.5, 166. , 166.5, 167. , 167.5, 168. , 168.5, 169. , 169.5,\n       170. , 170.5, 171. , 171.5, 172. , 172.5, 173. , 173.5, 174. , 174.5,\n       175. , 175.5, 176. , 176.5, 177. , 177.5, 178. , 178.5, 179. , 179.5,\n       180. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b4f44e5-4de7-4509-8832-db63563d1239' class='xr-section-summary-in' type='checkbox'  ><label for='section-2b4f44e5-4de7-4509-8832-db63563d1239' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3fbd277e-1d09-473d-8f12-12a2bdb7a30d' class='xr-index-data-in' type='checkbox'/><label for='index-3fbd277e-1d09-473d-8f12-12a2bdb7a30d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2014-07-01 00:00:00&#x27;, &#x27;2014-07-01 06:00:00&#x27;,\n               &#x27;2014-07-01 12:00:00&#x27;, &#x27;2014-07-01 18:00:00&#x27;,\n               &#x27;2014-07-02 00:00:00&#x27;, &#x27;2014-07-02 06:00:00&#x27;,\n               &#x27;2014-07-02 12:00:00&#x27;, &#x27;2014-07-02 18:00:00&#x27;,\n               &#x27;2014-07-03 00:00:00&#x27;, &#x27;2014-07-03 06:00:00&#x27;,\n               ...\n               &#x27;2014-07-29 12:00:00&#x27;, &#x27;2014-07-29 18:00:00&#x27;,\n               &#x27;2014-07-30 00:00:00&#x27;, &#x27;2014-07-30 06:00:00&#x27;,\n               &#x27;2014-07-30 12:00:00&#x27;, &#x27;2014-07-30 18:00:00&#x27;,\n               &#x27;2014-07-31 00:00:00&#x27;, &#x27;2014-07-31 06:00:00&#x27;,\n               &#x27;2014-07-31 12:00:00&#x27;, &#x27;2014-07-31 18:00:00&#x27;],\n              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=124, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3ea5f9b1-af25-4869-8092-09293ed8543c' class='xr-index-data-in' type='checkbox'/><label for='index-3ea5f9b1-af25-4869-8092-09293ed8543c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([92500.0, 85000.0, 70000.0, 60000.0, 50000.0, 25000.0, 5000.0], dtype=&#x27;float64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b2254ec1-5e22-451f-89a3-999752bd658b' class='xr-index-data-in' type='checkbox'/><label for='index-b2254ec1-5e22-451f-89a3-999752bd658b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0,  0.5,  1.0,  1.5,  2.0,  2.5,  3.0,  3.5,  4.0,  4.5,\n       ...\n       55.5, 56.0, 56.5, 57.0, 57.5, 58.0, 58.5, 59.0, 59.5, 60.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8c2adb14-e970-41fe-b20f-a4fe4c0948e1' class='xr-index-data-in' type='checkbox'/><label for='index-8c2adb14-e970-41fe-b20f-a4fe4c0948e1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100.0, 100.5, 101.0, 101.5, 102.0, 102.5, 103.0, 103.5, 104.0, 104.5,\n       ...\n       175.5, 176.0, 176.5, 177.0, 177.5, 178.0, 178.5, 179.0, 179.5, 180.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=161))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e2216bd1-a660-4cf7-b55e-5c9a25fbea1e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2216bd1-a660-4cf7-b55e-5c9a25fbea1e' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Air Temperature</dd><dt><span>comment :</span></dt><dd>Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>original_name :</span></dt><dd>t</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2017-09-01T06:33:19Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20). 2017-09-01T06:33:19Z altered by CMOR: Inverted axis: lat.</dd></dl></div></li></ul></div></div>"},"metadata":{},"execution_count":8}],"execution_count":8},{"cell_type":"markdown","metadata":{"id":"4E1AC1BEE63642988B37F4E1D1061FDB","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"#### 850hPa"},{"cell_type":"code","metadata":{"id":"D79264C38DD34488B4E3F251ABEC6F7D","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 50],crs=ccrs.PlateCarree())\nplt.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels=False                               \ngl.right_labels=False\n\nim = ax.contourf(lon, lat, ta.sel(time='2014-7-23 12:00',plev=85000), \n                 np.arange(285,301,1),\n                 extend='both',\n                 cmap=cmaps.MPL_Oranges, \n                 transform=ccrs.PlateCarree())\n\ncb = fig.colorbar(im, \n                  ticks=np.arange(285,305,5), \n                  orientation='vertical', \n                  extend='both', shrink=0.6,\n                  fraction=0.03, pad=0.02) \ncb.set_label(label='Temperature (K)', size=15)\ncb.ax.tick_params(labelsize=15)\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('850 hPa',loc='left',fontsize=15)\nplt.title(str(ta.sel(time='2014-7-23 12:00').time.values)[0:16],loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/D79264C38DD34488B4E3F251ABEC6F7D/six1c9m5mm.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":9},{"cell_type":"markdown","metadata":{"id":"F5E123059A0846B597006BE398560167","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"#### 500hPa"},{"cell_type":"code","metadata":{"trusted":true,"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"4FC61B519BE24DD590C9913A15FBDA95","scrolled":false,"notebookId":"66cec22aeb486dd4e9a64332"},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 50],crs=ccrs.PlateCarree())\nax.coastlines()\nplt.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels=False                               \ngl.right_labels=False\n\nim = ax.contourf(lon, lat, ta.sel(time='2014-7-23 12:00',plev=50000), \n                 np.arange(260,281,1),\n                 extend='both',\n                 cmap=cmaps.MPL_Oranges, \n                 transform=ccrs.PlateCarree())\n\ncb = fig.colorbar(im, \n                  ticks=np.arange(260,285,5), \n                  orientation='vertical', \n                  extend='both', shrink=0.6,\n                  fraction=0.03, pad=0.02) \ncb.set_label(label='Temperature (K)', size=15)\ncb.ax.tick_params(labelsize=15)\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('500 hPa',loc='left',fontsize=15)\nplt.title(str(ta.sel(time='2014-7-23 12:00').time.values)[0:16],loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/4FC61B519BE24DD590C9913A15FBDA95/six1calazr.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":10},{"cell_type":"markdown","metadata":{"id":"9961BE9C56AB49419AF26445F8502C6E","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"#### 250hPa"},{"cell_type":"code","metadata":{"trusted":true,"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"16BEDEF83DF24B65ABB0E52615CECDCB","scrolled":false,"notebookId":"66cec22aeb486dd4e9a64332"},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 50],crs=ccrs.PlateCarree())\nplt.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels=False                               \ngl.right_labels=False\n\nim = ax.contourf(lon, lat, ta.sel(time='2014-7-23 12:00',plev=25000), \n                 np.arange(230,246,1),\n                 extend='both',\n                 cmap=cmaps.MPL_Oranges, \n                 transform=ccrs.PlateCarree())\n\ncb = fig.colorbar(im, \n                  ticks=np.arange(230,250,5), \n                  orientation='vertical', \n                  extend='both', shrink=0.6,\n                  fraction=0.03, pad=0.02) \ncb.set_label(label='Temperature (K)', size=15)\ncb.ax.tick_params(labelsize=15)\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('250 hPa',loc='left',fontsize=15)\nplt.title(str(ta.sel(time='2014-7-23 12:00').time.values)[0:16],loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/16BEDEF83DF24B65ABB0E52615CECDCB/six1ca41vi.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":11},{"cell_type":"markdown","metadata":{"id":"9E4E90FCAE9C444F96349B5DA4BD34D2","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"### 风场"},{"cell_type":"code","metadata":{"id":"F6FB4ABD57BD446983AAB38D14C63650","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 读取经向风\nds = xr.open_dataset('/home/mw/input/typhoon/data/train/ua_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc')\nua = ds.ua\nua","outputs":[{"output_type":"execute_result","data":{"text/plain":"<xarray.DataArray 'ua' (time: 124, plev: 7, lat: 121, lon: 161)> Size: 68MB\n[16909508 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:   eastward_wind\n    long_name:       Eastward Wind\n    units:           m s-1\n    original_name:   u\n    original_units:  m*s-1\n    history:         2017-09-01T06:46:25Z altered by CMOR: Converted units fr...\n    cell_methods:    area: mean time: point\n    cell_measures:   area: areacella","text/html":"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n<defs>\n<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n</symbol>\n<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 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label {\n  color: var(--xr-font-color2);\n}\n\n.xr-section-summary-in + label:before {\n  display: inline-block;\n  content: '►';\n  font-size: 11px;\n  width: 15px;\n  text-align: center;\n}\n\n.xr-section-summary-in:disabled + label:before {\n  color: var(--xr-disabled-color);\n}\n\n.xr-section-summary-in:checked + label:before {\n  content: '▼';\n}\n\n.xr-section-summary-in:checked + label > span {\n  display: none;\n}\n\n.xr-section-summary,\n.xr-section-inline-details {\n  padding-top: 4px;\n  padding-bottom: 4px;\n}\n\n.xr-section-inline-details {\n  grid-column: 2 / -1;\n}\n\n.xr-section-details {\n  display: none;\n  grid-column: 1 / -1;\n  margin-bottom: 5px;\n}\n\n.xr-section-summary-in:checked ~ .xr-section-details {\n  display: contents;\n}\n\n.xr-array-wrap {\n  grid-column: 1 / -1;\n  display: grid;\n  grid-template-columns: 20px auto;\n}\n\n.xr-array-wrap > label {\n  grid-column: 1;\n  vertical-align: top;\n}\n\n.xr-preview {\n  color: var(--xr-font-color3);\n}\n\n.xr-array-preview,\n.xr-array-data {\n  padding: 0 5px !important;\n  grid-column: 2;\n}\n\n.xr-array-data,\n.xr-array-in:checked ~ .xr-array-preview {\n  display: none;\n}\n\n.xr-array-in:checked ~ .xr-array-data,\n.xr-array-preview {\n  display: inline-block;\n}\n\n.xr-dim-list {\n  display: inline-block !important;\n  list-style: none;\n  padding: 0 !important;\n  margin: 0;\n}\n\n.xr-dim-list li {\n  display: inline-block;\n  padding: 0;\n  margin: 0;\n}\n\n.xr-dim-list:before {\n  content: '(';\n}\n\n.xr-dim-list:after {\n  content: ')';\n}\n\n.xr-dim-list li:not(:last-child):after {\n  content: ',';\n  padding-right: 5px;\n}\n\n.xr-has-index {\n  font-weight: bold;\n}\n\n.xr-var-list,\n.xr-var-item {\n  display: contents;\n}\n\n.xr-var-item > div,\n.xr-var-item label,\n.xr-var-item > .xr-var-name span {\n  background-color: var(--xr-background-color-row-even);\n  margin-bottom: 0;\n}\n\n.xr-var-item > .xr-var-name:hover span {\n  padding-right: 5px;\n}\n\n.xr-var-list > li:nth-child(odd) > div,\n.xr-var-list > li:nth-child(odd) > label,\n.xr-var-list > li:nth-child(odd) > .xr-var-name span {\n  background-color: var(--xr-background-color-row-odd);\n}\n\n.xr-var-name {\n  grid-column: 1;\n}\n\n.xr-var-dims {\n  grid-column: 2;\n}\n\n.xr-var-dtype {\n  grid-column: 3;\n  text-align: right;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-preview {\n  grid-column: 4;\n}\n\n.xr-index-preview {\n  grid-column: 2 / 5;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-name,\n.xr-var-dims,\n.xr-var-dtype,\n.xr-preview,\n.xr-attrs dt {\n  white-space: nowrap;\n  overflow: hidden;\n  text-overflow: ellipsis;\n  padding-right: 10px;\n}\n\n.xr-var-name:hover,\n.xr-var-dims:hover,\n.xr-var-dtype:hover,\n.xr-attrs dt:hover {\n  overflow: visible;\n  width: auto;\n  z-index: 1;\n}\n\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  display: none;\n  background-color: var(--xr-background-color) !important;\n  padding-bottom: 5px !important;\n}\n\n.xr-var-attrs-in:checked ~ .xr-var-attrs,\n.xr-var-data-in:checked ~ .xr-var-data,\n.xr-index-data-in:checked ~ .xr-index-data {\n  display: block;\n}\n\n.xr-var-data > table {\n  float: right;\n}\n\n.xr-var-name span,\n.xr-var-data,\n.xr-index-name div,\n.xr-index-data,\n.xr-attrs {\n  padding-left: 25px !important;\n}\n\n.xr-attrs,\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  grid-column: 1 / -1;\n}\n\ndl.xr-attrs {\n  padding: 0;\n  margin: 0;\n  display: grid;\n  grid-template-columns: 125px auto;\n}\n\n.xr-attrs dt,\n.xr-attrs dd {\n  padding: 0;\n  margin: 0;\n  float: left;\n  padding-right: 10px;\n  width: auto;\n}\n\n.xr-attrs dt {\n  font-weight: normal;\n  grid-column: 1;\n}\n\n.xr-attrs dt:hover span {\n  display: inline-block;\n  background: var(--xr-background-color);\n  padding-right: 10px;\n}\n\n.xr-attrs dd {\n  grid-column: 2;\n  white-space: pre-wrap;\n  word-break: break-all;\n}\n\n.xr-icon-database,\n.xr-icon-file-text2,\n.xr-no-icon {\n  display: inline-block;\n  vertical-align: middle;\n  width: 1em;\n  height: 1.5em !important;\n  stroke-width: 0;\n  stroke: currentColor;\n  fill: currentColor;\n}\n</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;ua&#x27; (time: 124, plev: 7, lat: 121, lon: 161)&gt; Size: 68MB\n[16909508 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:   eastward_wind\n    long_name:       Eastward Wind\n    units:           m s-1\n    original_name:   u\n    original_units:  m*s-1\n    history:         2017-09-01T06:46:25Z altered by CMOR: Converted units fr...\n    cell_methods:    area: mean time: point\n    cell_measures:   area: areacella</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ua'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 124</li><li><span class='xr-has-index'>plev</span>: 7</li><li><span class='xr-has-index'>lat</span>: 121</li><li><span class='xr-has-index'>lon</span>: 161</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-876367ef-32b1-4bb6-a7b0-0a51b92baa36' class='xr-array-in' type='checkbox' checked><label for='section-876367ef-32b1-4bb6-a7b0-0a51b92baa36' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[16909508 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-430266d9-86ae-4e21-8108-0a42e70e5dff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-430266d9-86ae-4e21-8108-0a42e70e5dff' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2014-07-01 ... 2014-07-31T18:00:00</div><input id='attrs-77aa1961-37e0-4ae2-af30-0f1e682824cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77aa1961-37e0-4ae2-af30-0f1e682824cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-106c3cdd-973e-4e06-ac3a-8a7a2604ccf2' class='xr-var-data-in' type='checkbox'><label for='data-106c3cdd-973e-4e06-ac3a-8a7a2604ccf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2014-07-01T00:00:00.000000000&#x27;, &#x27;2014-07-01T06:00:00.000000000&#x27;,\n       &#x27;2014-07-01T12:00:00.000000000&#x27;, &#x27;2014-07-01T18:00:00.000000000&#x27;,\n       &#x27;2014-07-02T00:00:00.000000000&#x27;, &#x27;2014-07-02T06:00:00.000000000&#x27;,\n       &#x27;2014-07-02T12:00:00.000000000&#x27;, &#x27;2014-07-02T18:00:00.000000000&#x27;,\n       &#x27;2014-07-03T00:00:00.000000000&#x27;, &#x27;2014-07-03T06:00:00.000000000&#x27;,\n       &#x27;2014-07-03T12:00:00.000000000&#x27;, &#x27;2014-07-03T18:00:00.000000000&#x27;,\n       &#x27;2014-07-04T00:00:00.000000000&#x27;, &#x27;2014-07-04T06:00:00.000000000&#x27;,\n       &#x27;2014-07-04T12:00:00.000000000&#x27;, &#x27;2014-07-04T18:00:00.000000000&#x27;,\n       &#x27;2014-07-05T00:00:00.000000000&#x27;, &#x27;2014-07-05T06:00:00.000000000&#x27;,\n       &#x27;2014-07-05T12:00:00.000000000&#x27;, &#x27;2014-07-05T18:00:00.000000000&#x27;,\n       &#x27;2014-07-06T00:00:00.000000000&#x27;, &#x27;2014-07-06T06:00:00.000000000&#x27;,\n       &#x27;2014-07-06T12:00:00.000000000&#x27;, &#x27;2014-07-06T18:00:00.000000000&#x27;,\n       &#x27;2014-07-07T00:00:00.000000000&#x27;, &#x27;2014-07-07T06:00:00.000000000&#x27;,\n       &#x27;2014-07-07T12:00:00.000000000&#x27;, &#x27;2014-07-07T18:00:00.000000000&#x27;,\n       &#x27;2014-07-08T00:00:00.000000000&#x27;, &#x27;2014-07-08T06:00:00.000000000&#x27;,\n       &#x27;2014-07-08T12:00:00.000000000&#x27;, &#x27;2014-07-08T18:00:00.000000000&#x27;,\n       &#x27;2014-07-09T00:00:00.000000000&#x27;, &#x27;2014-07-09T06:00:00.000000000&#x27;,\n       &#x27;2014-07-09T12:00:00.000000000&#x27;, &#x27;2014-07-09T18:00:00.000000000&#x27;,\n       &#x27;2014-07-10T00:00:00.000000000&#x27;, &#x27;2014-07-10T06:00:00.000000000&#x27;,\n       &#x27;2014-07-10T12:00:00.000000000&#x27;, &#x27;2014-07-10T18:00:00.000000000&#x27;,\n       &#x27;2014-07-11T00:00:00.000000000&#x27;, &#x27;2014-07-11T06:00:00.000000000&#x27;,\n       &#x27;2014-07-11T12:00:00.000000000&#x27;, &#x27;2014-07-11T18:00:00.000000000&#x27;,\n       &#x27;2014-07-12T00:00:00.000000000&#x27;, &#x27;2014-07-12T06:00:00.000000000&#x27;,\n       &#x27;2014-07-12T12:00:00.000000000&#x27;, &#x27;2014-07-12T18:00:00.000000000&#x27;,\n       &#x27;2014-07-13T00:00:00.000000000&#x27;, &#x27;2014-07-13T06:00:00.000000000&#x27;,\n       &#x27;2014-07-13T12:00:00.000000000&#x27;, &#x27;2014-07-13T18:00:00.000000000&#x27;,\n       &#x27;2014-07-14T00:00:00.000000000&#x27;, &#x27;2014-07-14T06:00:00.000000000&#x27;,\n       &#x27;2014-07-14T12:00:00.000000000&#x27;, &#x27;2014-07-14T18:00:00.000000000&#x27;,\n       &#x27;2014-07-15T00:00:00.000000000&#x27;, &#x27;2014-07-15T06:00:00.000000000&#x27;,\n       &#x27;2014-07-15T12:00:00.000000000&#x27;, &#x27;2014-07-15T18:00:00.000000000&#x27;,\n       &#x27;2014-07-16T00:00:00.000000000&#x27;, &#x27;2014-07-16T06:00:00.000000000&#x27;,\n       &#x27;2014-07-16T12:00:00.000000000&#x27;, &#x27;2014-07-16T18:00:00.000000000&#x27;,\n       &#x27;2014-07-17T00:00:00.000000000&#x27;, &#x27;2014-07-17T06:00:00.000000000&#x27;,\n       &#x27;2014-07-17T12:00:00.000000000&#x27;, &#x27;2014-07-17T18:00:00.000000000&#x27;,\n       &#x27;2014-07-18T00:00:00.000000000&#x27;, &#x27;2014-07-18T06:00:00.000000000&#x27;,\n       &#x27;2014-07-18T12:00:00.000000000&#x27;, &#x27;2014-07-18T18:00:00.000000000&#x27;,\n       &#x27;2014-07-19T00:00:00.000000000&#x27;, &#x27;2014-07-19T06:00:00.000000000&#x27;,\n       &#x27;2014-07-19T12:00:00.000000000&#x27;, &#x27;2014-07-19T18:00:00.000000000&#x27;,\n       &#x27;2014-07-20T00:00:00.000000000&#x27;, &#x27;2014-07-20T06:00:00.000000000&#x27;,\n       &#x27;2014-07-20T12:00:00.000000000&#x27;, &#x27;2014-07-20T18:00:00.000000000&#x27;,\n       &#x27;2014-07-21T00:00:00.000000000&#x27;, &#x27;2014-07-21T06:00:00.000000000&#x27;,\n       &#x27;2014-07-21T12:00:00.000000000&#x27;, &#x27;2014-07-21T18:00:00.000000000&#x27;,\n       &#x27;2014-07-22T00:00:00.000000000&#x27;, &#x27;2014-07-22T06:00:00.000000000&#x27;,\n       &#x27;2014-07-22T12:00:00.000000000&#x27;, &#x27;2014-07-22T18:00:00.000000000&#x27;,\n       &#x27;2014-07-23T00:00:00.000000000&#x27;, &#x27;2014-07-23T06:00:00.000000000&#x27;,\n       &#x27;2014-07-23T12:00:00.000000000&#x27;, &#x27;2014-07-23T18:00:00.000000000&#x27;,\n       &#x27;2014-07-24T00:00:00.000000000&#x27;, &#x27;2014-07-24T06:00:00.000000000&#x27;,\n       &#x27;2014-07-24T12:00:00.000000000&#x27;, &#x27;2014-07-24T18:00:00.000000000&#x27;,\n       &#x27;2014-07-25T00:00:00.000000000&#x27;, &#x27;2014-07-25T06:00:00.000000000&#x27;,\n       &#x27;2014-07-25T12:00:00.000000000&#x27;, &#x27;2014-07-25T18:00:00.000000000&#x27;,\n       &#x27;2014-07-26T00:00:00.000000000&#x27;, &#x27;2014-07-26T06:00:00.000000000&#x27;,\n       &#x27;2014-07-26T12:00:00.000000000&#x27;, &#x27;2014-07-26T18:00:00.000000000&#x27;,\n       &#x27;2014-07-27T00:00:00.000000000&#x27;, &#x27;2014-07-27T06:00:00.000000000&#x27;,\n       &#x27;2014-07-27T12:00:00.000000000&#x27;, &#x27;2014-07-27T18:00:00.000000000&#x27;,\n       &#x27;2014-07-28T00:00:00.000000000&#x27;, &#x27;2014-07-28T06:00:00.000000000&#x27;,\n       &#x27;2014-07-28T12:00:00.000000000&#x27;, &#x27;2014-07-28T18:00:00.000000000&#x27;,\n       &#x27;2014-07-29T00:00:00.000000000&#x27;, &#x27;2014-07-29T06:00:00.000000000&#x27;,\n       &#x27;2014-07-29T12:00:00.000000000&#x27;, &#x27;2014-07-29T18:00:00.000000000&#x27;,\n       &#x27;2014-07-30T00:00:00.000000000&#x27;, &#x27;2014-07-30T06:00:00.000000000&#x27;,\n       &#x27;2014-07-30T12:00:00.000000000&#x27;, &#x27;2014-07-30T18:00:00.000000000&#x27;,\n       &#x27;2014-07-31T00:00:00.000000000&#x27;, &#x27;2014-07-31T06:00:00.000000000&#x27;,\n       &#x27;2014-07-31T12:00:00.000000000&#x27;, &#x27;2014-07-31T18:00:00.000000000&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.25e+04 8.5e+04 ... 2.5e+04 5e+03</div><input id='attrs-883da429-c27e-4900-b28a-cb589cab5ac1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-883da429-c27e-4900-b28a-cb589cab5ac1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e8e2578-c44c-46da-9954-565ac6d5d7de' class='xr-var-data-in' type='checkbox'><label for='data-2e8e2578-c44c-46da-9954-565ac6d5d7de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([92500., 85000., 70000., 60000., 50000., 25000.,  5000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.5 1.0 1.5 ... 59.0 59.5 60.0</div><input id='attrs-94b7505a-fa7d-4b15-8d38-ebae34481a38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94b7505a-fa7d-4b15-8d38-ebae34481a38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5b7fca5-f199-4be5-bf10-7dbe96c4022c' class='xr-var-data-in' type='checkbox'><label for='data-b5b7fca5-f199-4be5-bf10-7dbe96c4022c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,\n        6. ,  6.5,  7. ,  7.5,  8. ,  8.5,  9. ,  9.5, 10. , 10.5, 11. , 11.5,\n       12. , 12.5, 13. , 13.5, 14. , 14.5, 15. , 15.5, 16. , 16.5, 17. , 17.5,\n       18. , 18.5, 19. , 19.5, 20. , 20.5, 21. , 21.5, 22. , 22.5, 23. , 23.5,\n       24. , 24.5, 25. , 25.5, 26. , 26.5, 27. , 27.5, 28. , 28.5, 29. , 29.5,\n       30. , 30.5, 31. , 31.5, 32. , 32.5, 33. , 33.5, 34. , 34.5, 35. , 35.5,\n       36. , 36.5, 37. , 37.5, 38. , 38.5, 39. , 39.5, 40. , 40.5, 41. , 41.5,\n       42. , 42.5, 43. , 43.5, 44. , 44.5, 45. , 45.5, 46. , 46.5, 47. , 47.5,\n       48. , 48.5, 49. , 49.5, 50. , 50.5, 51. , 51.5, 52. , 52.5, 53. , 53.5,\n       54. , 54.5, 55. , 55.5, 56. , 56.5, 57. , 57.5, 58. , 58.5, 59. , 59.5,\n       60. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.5 101.0 ... 179.5 180.0</div><input id='attrs-beef9454-ae65-45f6-a08e-19e03c007294' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-beef9454-ae65-45f6-a08e-19e03c007294' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8be7dd66-9e70-4f1b-b1e4-e22ecfddf5ce' class='xr-var-data-in' type='checkbox'><label for='data-8be7dd66-9e70-4f1b-b1e4-e22ecfddf5ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.5, 101. , 101.5, 102. , 102.5, 103. , 103.5, 104. , 104.5,\n       105. , 105.5, 106. , 106.5, 107. , 107.5, 108. , 108.5, 109. , 109.5,\n       110. , 110.5, 111. , 111.5, 112. , 112.5, 113. , 113.5, 114. , 114.5,\n       115. , 115.5, 116. , 116.5, 117. , 117.5, 118. , 118.5, 119. , 119.5,\n       120. , 120.5, 121. , 121.5, 122. , 122.5, 123. , 123.5, 124. , 124.5,\n       125. , 125.5, 126. , 126.5, 127. , 127.5, 128. , 128.5, 129. , 129.5,\n       130. , 130.5, 131. , 131.5, 132. , 132.5, 133. , 133.5, 134. , 134.5,\n       135. , 135.5, 136. , 136.5, 137. , 137.5, 138. , 138.5, 139. , 139.5,\n       140. , 140.5, 141. , 141.5, 142. , 142.5, 143. , 143.5, 144. , 144.5,\n       145. , 145.5, 146. , 146.5, 147. , 147.5, 148. , 148.5, 149. , 149.5,\n       150. , 150.5, 151. , 151.5, 152. , 152.5, 153. , 153.5, 154. , 154.5,\n       155. , 155.5, 156. , 156.5, 157. , 157.5, 158. , 158.5, 159. , 159.5,\n       160. , 160.5, 161. , 161.5, 162. , 162.5, 163. , 163.5, 164. , 164.5,\n       165. , 165.5, 166. , 166.5, 167. , 167.5, 168. , 168.5, 169. , 169.5,\n       170. , 170.5, 171. , 171.5, 172. , 172.5, 173. , 173.5, 174. , 174.5,\n       175. , 175.5, 176. , 176.5, 177. , 177.5, 178. , 178.5, 179. , 179.5,\n       180. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0add7dd4-6700-4bb4-81f7-eb0399b53434' class='xr-section-summary-in' type='checkbox'  ><label for='section-0add7dd4-6700-4bb4-81f7-eb0399b53434' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-555e9a46-5814-4c61-b570-095333aa107f' class='xr-index-data-in' type='checkbox'/><label for='index-555e9a46-5814-4c61-b570-095333aa107f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2014-07-01 00:00:00&#x27;, &#x27;2014-07-01 06:00:00&#x27;,\n               &#x27;2014-07-01 12:00:00&#x27;, &#x27;2014-07-01 18:00:00&#x27;,\n               &#x27;2014-07-02 00:00:00&#x27;, &#x27;2014-07-02 06:00:00&#x27;,\n               &#x27;2014-07-02 12:00:00&#x27;, &#x27;2014-07-02 18:00:00&#x27;,\n               &#x27;2014-07-03 00:00:00&#x27;, &#x27;2014-07-03 06:00:00&#x27;,\n               ...\n               &#x27;2014-07-29 12:00:00&#x27;, &#x27;2014-07-29 18:00:00&#x27;,\n               &#x27;2014-07-30 00:00:00&#x27;, &#x27;2014-07-30 06:00:00&#x27;,\n               &#x27;2014-07-30 12:00:00&#x27;, &#x27;2014-07-30 18:00:00&#x27;,\n               &#x27;2014-07-31 00:00:00&#x27;, &#x27;2014-07-31 06:00:00&#x27;,\n               &#x27;2014-07-31 12:00:00&#x27;, &#x27;2014-07-31 18:00:00&#x27;],\n              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=124, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f9741948-b1b7-475e-826d-a363a7570259' class='xr-index-data-in' type='checkbox'/><label for='index-f9741948-b1b7-475e-826d-a363a7570259' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([92500.0, 85000.0, 70000.0, 60000.0, 50000.0, 25000.0, 5000.0], dtype=&#x27;float64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-043c2838-50e2-48c2-86e1-91c91e9ef1ce' class='xr-index-data-in' type='checkbox'/><label for='index-043c2838-50e2-48c2-86e1-91c91e9ef1ce' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0,  0.5,  1.0,  1.5,  2.0,  2.5,  3.0,  3.5,  4.0,  4.5,\n       ...\n       55.5, 56.0, 56.5, 57.0, 57.5, 58.0, 58.5, 59.0, 59.5, 60.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-10611a4c-5c28-4da7-bdaa-c5eb153e9e65' class='xr-index-data-in' type='checkbox'/><label for='index-10611a4c-5c28-4da7-bdaa-c5eb153e9e65' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100.0, 100.5, 101.0, 101.5, 102.0, 102.5, 103.0, 103.5, 104.0, 104.5,\n       ...\n       175.5, 176.0, 176.5, 177.0, 177.5, 178.0, 178.5, 179.0, 179.5, 180.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=161))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-94d3d4d5-010a-4cd4-a477-75b80ee374ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-94d3d4d5-010a-4cd4-a477-75b80ee374ef' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>eastward_wind</dd><dt><span>long_name :</span></dt><dd>Eastward Wind</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>original_name :</span></dt><dd>u</dd><dt><span>original_units :</span></dt><dd>m*s-1</dd><dt><span>history :</span></dt><dd>2017-09-01T06:46:25Z altered by CMOR: Converted units from &#x27;m*s-1&#x27; to &#x27;m s-1&#x27;. 2017-09-01T06:46:25Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20). 2017-09-01T06:46:25Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div></li></ul></div></div>"},"metadata":{},"execution_count":12}],"execution_count":12},{"cell_type":"code","metadata":{"id":"8A57B8F863EF4ACD99ED379A19E40F7D","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 读取纬向风\nds = xr.open_dataset('/home/mw/input/typhoon/data/train/va_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc')\nva = ds.va\nva","outputs":[{"output_type":"execute_result","data":{"text/plain":"<xarray.DataArray 'va' (time: 124, plev: 7, lat: 121, lon: 161)> Size: 68MB\n[16909508 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:   northward_wind\n    long_name:       Northward Wind\n    units:           m s-1\n    original_name:   v\n    original_units:  m*s-1\n    history:         2017-09-01T06:58:04Z altered by CMOR: Converted units fr...\n    cell_methods:    area: mean time: point\n    cell_measures:   area: areacella","text/html":"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n<defs>\n<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n</symbol>\n<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n<path d=\"M28.681 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background-color: var(--xr-background-color-row-even);\n  margin-bottom: 0;\n}\n\n.xr-var-item > .xr-var-name:hover span {\n  padding-right: 5px;\n}\n\n.xr-var-list > li:nth-child(odd) > div,\n.xr-var-list > li:nth-child(odd) > label,\n.xr-var-list > li:nth-child(odd) > .xr-var-name span {\n  background-color: var(--xr-background-color-row-odd);\n}\n\n.xr-var-name {\n  grid-column: 1;\n}\n\n.xr-var-dims {\n  grid-column: 2;\n}\n\n.xr-var-dtype {\n  grid-column: 3;\n  text-align: right;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-preview {\n  grid-column: 4;\n}\n\n.xr-index-preview {\n  grid-column: 2 / 5;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-name,\n.xr-var-dims,\n.xr-var-dtype,\n.xr-preview,\n.xr-attrs dt {\n  white-space: nowrap;\n  overflow: hidden;\n  text-overflow: ellipsis;\n  padding-right: 10px;\n}\n\n.xr-var-name:hover,\n.xr-var-dims:hover,\n.xr-var-dtype:hover,\n.xr-attrs dt:hover {\n  overflow: visible;\n  width: auto;\n  z-index: 1;\n}\n\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  display: none;\n  background-color: var(--xr-background-color) !important;\n  padding-bottom: 5px !important;\n}\n\n.xr-var-attrs-in:checked ~ .xr-var-attrs,\n.xr-var-data-in:checked ~ .xr-var-data,\n.xr-index-data-in:checked ~ .xr-index-data {\n  display: block;\n}\n\n.xr-var-data > table {\n  float: right;\n}\n\n.xr-var-name span,\n.xr-var-data,\n.xr-index-name div,\n.xr-index-data,\n.xr-attrs {\n  padding-left: 25px !important;\n}\n\n.xr-attrs,\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  grid-column: 1 / -1;\n}\n\ndl.xr-attrs {\n  padding: 0;\n  margin: 0;\n  display: grid;\n  grid-template-columns: 125px auto;\n}\n\n.xr-attrs dt,\n.xr-attrs dd {\n  padding: 0;\n  margin: 0;\n  float: left;\n  padding-right: 10px;\n  width: auto;\n}\n\n.xr-attrs dt {\n  font-weight: normal;\n  grid-column: 1;\n}\n\n.xr-attrs dt:hover span {\n  display: inline-block;\n  background: var(--xr-background-color);\n  padding-right: 10px;\n}\n\n.xr-attrs dd {\n  grid-column: 2;\n  white-space: pre-wrap;\n  word-break: break-all;\n}\n\n.xr-icon-database,\n.xr-icon-file-text2,\n.xr-no-icon {\n  display: inline-block;\n  vertical-align: middle;\n  width: 1em;\n  height: 1.5em !important;\n  stroke-width: 0;\n  stroke: currentColor;\n  fill: currentColor;\n}\n</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;va&#x27; (time: 124, plev: 7, lat: 121, lon: 161)&gt; Size: 68MB\n[16909508 values with dtype=float32]\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0\nAttributes:\n    standard_name:   northward_wind\n    long_name:       Northward Wind\n    units:           m s-1\n    original_name:   v\n    original_units:  m*s-1\n    history:         2017-09-01T06:58:04Z altered by CMOR: Converted units fr...\n    cell_methods:    area: mean time: point\n    cell_measures:   area: areacella</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'va'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 124</li><li><span class='xr-has-index'>plev</span>: 7</li><li><span class='xr-has-index'>lat</span>: 121</li><li><span class='xr-has-index'>lon</span>: 161</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-efd05066-d3b1-432a-b33f-6a74252b4ac9' class='xr-array-in' type='checkbox' checked><label for='section-efd05066-d3b1-432a-b33f-6a74252b4ac9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[16909508 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-3fcaf91c-0b12-4f33-9ebe-6a03c66c88b0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3fcaf91c-0b12-4f33-9ebe-6a03c66c88b0' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2014-07-01 ... 2014-07-31T18:00:00</div><input id='attrs-b6dee118-de4f-47d5-aeb0-1ba13292c814' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6dee118-de4f-47d5-aeb0-1ba13292c814' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a16c914-9fd8-4689-a1f9-cfd3e0173367' class='xr-var-data-in' type='checkbox'><label for='data-4a16c914-9fd8-4689-a1f9-cfd3e0173367' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2014-07-01T00:00:00.000000000&#x27;, &#x27;2014-07-01T06:00:00.000000000&#x27;,\n       &#x27;2014-07-01T12:00:00.000000000&#x27;, &#x27;2014-07-01T18:00:00.000000000&#x27;,\n       &#x27;2014-07-02T00:00:00.000000000&#x27;, &#x27;2014-07-02T06:00:00.000000000&#x27;,\n       &#x27;2014-07-02T12:00:00.000000000&#x27;, &#x27;2014-07-02T18:00:00.000000000&#x27;,\n       &#x27;2014-07-03T00:00:00.000000000&#x27;, &#x27;2014-07-03T06:00:00.000000000&#x27;,\n       &#x27;2014-07-03T12:00:00.000000000&#x27;, &#x27;2014-07-03T18:00:00.000000000&#x27;,\n       &#x27;2014-07-04T00:00:00.000000000&#x27;, &#x27;2014-07-04T06:00:00.000000000&#x27;,\n       &#x27;2014-07-04T12:00:00.000000000&#x27;, &#x27;2014-07-04T18:00:00.000000000&#x27;,\n       &#x27;2014-07-05T00:00:00.000000000&#x27;, &#x27;2014-07-05T06:00:00.000000000&#x27;,\n       &#x27;2014-07-05T12:00:00.000000000&#x27;, &#x27;2014-07-05T18:00:00.000000000&#x27;,\n       &#x27;2014-07-06T00:00:00.000000000&#x27;, &#x27;2014-07-06T06:00:00.000000000&#x27;,\n       &#x27;2014-07-06T12:00:00.000000000&#x27;, &#x27;2014-07-06T18:00:00.000000000&#x27;,\n       &#x27;2014-07-07T00:00:00.000000000&#x27;, &#x27;2014-07-07T06:00:00.000000000&#x27;,\n       &#x27;2014-07-07T12:00:00.000000000&#x27;, &#x27;2014-07-07T18:00:00.000000000&#x27;,\n       &#x27;2014-07-08T00:00:00.000000000&#x27;, &#x27;2014-07-08T06:00:00.000000000&#x27;,\n       &#x27;2014-07-08T12:00:00.000000000&#x27;, &#x27;2014-07-08T18:00:00.000000000&#x27;,\n       &#x27;2014-07-09T00:00:00.000000000&#x27;, &#x27;2014-07-09T06:00:00.000000000&#x27;,\n       &#x27;2014-07-09T12:00:00.000000000&#x27;, &#x27;2014-07-09T18:00:00.000000000&#x27;,\n       &#x27;2014-07-10T00:00:00.000000000&#x27;, &#x27;2014-07-10T06:00:00.000000000&#x27;,\n       &#x27;2014-07-10T12:00:00.000000000&#x27;, &#x27;2014-07-10T18:00:00.000000000&#x27;,\n       &#x27;2014-07-11T00:00:00.000000000&#x27;, &#x27;2014-07-11T06:00:00.000000000&#x27;,\n       &#x27;2014-07-11T12:00:00.000000000&#x27;, &#x27;2014-07-11T18:00:00.000000000&#x27;,\n       &#x27;2014-07-12T00:00:00.000000000&#x27;, &#x27;2014-07-12T06:00:00.000000000&#x27;,\n       &#x27;2014-07-12T12:00:00.000000000&#x27;, &#x27;2014-07-12T18:00:00.000000000&#x27;,\n       &#x27;2014-07-13T00:00:00.000000000&#x27;, &#x27;2014-07-13T06:00:00.000000000&#x27;,\n       &#x27;2014-07-13T12:00:00.000000000&#x27;, &#x27;2014-07-13T18:00:00.000000000&#x27;,\n       &#x27;2014-07-14T00:00:00.000000000&#x27;, &#x27;2014-07-14T06:00:00.000000000&#x27;,\n       &#x27;2014-07-14T12:00:00.000000000&#x27;, &#x27;2014-07-14T18:00:00.000000000&#x27;,\n       &#x27;2014-07-15T00:00:00.000000000&#x27;, &#x27;2014-07-15T06:00:00.000000000&#x27;,\n       &#x27;2014-07-15T12:00:00.000000000&#x27;, &#x27;2014-07-15T18:00:00.000000000&#x27;,\n       &#x27;2014-07-16T00:00:00.000000000&#x27;, &#x27;2014-07-16T06:00:00.000000000&#x27;,\n       &#x27;2014-07-16T12:00:00.000000000&#x27;, &#x27;2014-07-16T18:00:00.000000000&#x27;,\n       &#x27;2014-07-17T00:00:00.000000000&#x27;, &#x27;2014-07-17T06:00:00.000000000&#x27;,\n       &#x27;2014-07-17T12:00:00.000000000&#x27;, &#x27;2014-07-17T18:00:00.000000000&#x27;,\n       &#x27;2014-07-18T00:00:00.000000000&#x27;, &#x27;2014-07-18T06:00:00.000000000&#x27;,\n       &#x27;2014-07-18T12:00:00.000000000&#x27;, &#x27;2014-07-18T18:00:00.000000000&#x27;,\n       &#x27;2014-07-19T00:00:00.000000000&#x27;, &#x27;2014-07-19T06:00:00.000000000&#x27;,\n       &#x27;2014-07-19T12:00:00.000000000&#x27;, &#x27;2014-07-19T18:00:00.000000000&#x27;,\n       &#x27;2014-07-20T00:00:00.000000000&#x27;, &#x27;2014-07-20T06:00:00.000000000&#x27;,\n       &#x27;2014-07-20T12:00:00.000000000&#x27;, &#x27;2014-07-20T18:00:00.000000000&#x27;,\n       &#x27;2014-07-21T00:00:00.000000000&#x27;, &#x27;2014-07-21T06:00:00.000000000&#x27;,\n       &#x27;2014-07-21T12:00:00.000000000&#x27;, &#x27;2014-07-21T18:00:00.000000000&#x27;,\n       &#x27;2014-07-22T00:00:00.000000000&#x27;, &#x27;2014-07-22T06:00:00.000000000&#x27;,\n       &#x27;2014-07-22T12:00:00.000000000&#x27;, &#x27;2014-07-22T18:00:00.000000000&#x27;,\n       &#x27;2014-07-23T00:00:00.000000000&#x27;, &#x27;2014-07-23T06:00:00.000000000&#x27;,\n       &#x27;2014-07-23T12:00:00.000000000&#x27;, &#x27;2014-07-23T18:00:00.000000000&#x27;,\n       &#x27;2014-07-24T00:00:00.000000000&#x27;, &#x27;2014-07-24T06:00:00.000000000&#x27;,\n       &#x27;2014-07-24T12:00:00.000000000&#x27;, &#x27;2014-07-24T18:00:00.000000000&#x27;,\n       &#x27;2014-07-25T00:00:00.000000000&#x27;, &#x27;2014-07-25T06:00:00.000000000&#x27;,\n       &#x27;2014-07-25T12:00:00.000000000&#x27;, &#x27;2014-07-25T18:00:00.000000000&#x27;,\n       &#x27;2014-07-26T00:00:00.000000000&#x27;, &#x27;2014-07-26T06:00:00.000000000&#x27;,\n       &#x27;2014-07-26T12:00:00.000000000&#x27;, &#x27;2014-07-26T18:00:00.000000000&#x27;,\n       &#x27;2014-07-27T00:00:00.000000000&#x27;, &#x27;2014-07-27T06:00:00.000000000&#x27;,\n       &#x27;2014-07-27T12:00:00.000000000&#x27;, &#x27;2014-07-27T18:00:00.000000000&#x27;,\n       &#x27;2014-07-28T00:00:00.000000000&#x27;, &#x27;2014-07-28T06:00:00.000000000&#x27;,\n       &#x27;2014-07-28T12:00:00.000000000&#x27;, &#x27;2014-07-28T18:00:00.000000000&#x27;,\n       &#x27;2014-07-29T00:00:00.000000000&#x27;, &#x27;2014-07-29T06:00:00.000000000&#x27;,\n       &#x27;2014-07-29T12:00:00.000000000&#x27;, &#x27;2014-07-29T18:00:00.000000000&#x27;,\n       &#x27;2014-07-30T00:00:00.000000000&#x27;, &#x27;2014-07-30T06:00:00.000000000&#x27;,\n       &#x27;2014-07-30T12:00:00.000000000&#x27;, &#x27;2014-07-30T18:00:00.000000000&#x27;,\n       &#x27;2014-07-31T00:00:00.000000000&#x27;, &#x27;2014-07-31T06:00:00.000000000&#x27;,\n       &#x27;2014-07-31T12:00:00.000000000&#x27;, &#x27;2014-07-31T18:00:00.000000000&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.25e+04 8.5e+04 ... 2.5e+04 5e+03</div><input id='attrs-14c709e6-8e72-493e-b800-2e2e787d90f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14c709e6-8e72-493e-b800-2e2e787d90f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-322efb39-a80f-41aa-83a1-428663e2a8ca' class='xr-var-data-in' type='checkbox'><label for='data-322efb39-a80f-41aa-83a1-428663e2a8ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([92500., 85000., 70000., 60000., 50000., 25000.,  5000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.5 1.0 1.5 ... 59.0 59.5 60.0</div><input id='attrs-3b1b926a-dc72-49c0-b0b1-f06221c6660c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b1b926a-dc72-49c0-b0b1-f06221c6660c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5c198d5-8036-484b-af86-a4a11552e6a6' class='xr-var-data-in' type='checkbox'><label for='data-c5c198d5-8036-484b-af86-a4a11552e6a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,\n        6. ,  6.5,  7. ,  7.5,  8. ,  8.5,  9. ,  9.5, 10. , 10.5, 11. , 11.5,\n       12. , 12.5, 13. , 13.5, 14. , 14.5, 15. , 15.5, 16. , 16.5, 17. , 17.5,\n       18. , 18.5, 19. , 19.5, 20. , 20.5, 21. , 21.5, 22. , 22.5, 23. , 23.5,\n       24. , 24.5, 25. , 25.5, 26. , 26.5, 27. , 27.5, 28. , 28.5, 29. , 29.5,\n       30. , 30.5, 31. , 31.5, 32. , 32.5, 33. , 33.5, 34. , 34.5, 35. , 35.5,\n       36. , 36.5, 37. , 37.5, 38. , 38.5, 39. , 39.5, 40. , 40.5, 41. , 41.5,\n       42. , 42.5, 43. , 43.5, 44. , 44.5, 45. , 45.5, 46. , 46.5, 47. , 47.5,\n       48. , 48.5, 49. , 49.5, 50. , 50.5, 51. , 51.5, 52. , 52.5, 53. , 53.5,\n       54. , 54.5, 55. , 55.5, 56. , 56.5, 57. , 57.5, 58. , 58.5, 59. , 59.5,\n       60. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.5 101.0 ... 179.5 180.0</div><input id='attrs-02fcae14-4fcf-47e4-966c-889f4746bb6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02fcae14-4fcf-47e4-966c-889f4746bb6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-574daf12-a2cf-497e-bc27-7eb4591da415' class='xr-var-data-in' type='checkbox'><label for='data-574daf12-a2cf-497e-bc27-7eb4591da415' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.5, 101. , 101.5, 102. , 102.5, 103. , 103.5, 104. , 104.5,\n       105. , 105.5, 106. , 106.5, 107. , 107.5, 108. , 108.5, 109. , 109.5,\n       110. , 110.5, 111. , 111.5, 112. , 112.5, 113. , 113.5, 114. , 114.5,\n       115. , 115.5, 116. , 116.5, 117. , 117.5, 118. , 118.5, 119. , 119.5,\n       120. , 120.5, 121. , 121.5, 122. , 122.5, 123. , 123.5, 124. , 124.5,\n       125. , 125.5, 126. , 126.5, 127. , 127.5, 128. , 128.5, 129. , 129.5,\n       130. , 130.5, 131. , 131.5, 132. , 132.5, 133. , 133.5, 134. , 134.5,\n       135. , 135.5, 136. , 136.5, 137. , 137.5, 138. , 138.5, 139. , 139.5,\n       140. , 140.5, 141. , 141.5, 142. , 142.5, 143. , 143.5, 144. , 144.5,\n       145. , 145.5, 146. , 146.5, 147. , 147.5, 148. , 148.5, 149. , 149.5,\n       150. , 150.5, 151. , 151.5, 152. , 152.5, 153. , 153.5, 154. , 154.5,\n       155. , 155.5, 156. , 156.5, 157. , 157.5, 158. , 158.5, 159. , 159.5,\n       160. , 160.5, 161. , 161.5, 162. , 162.5, 163. , 163.5, 164. , 164.5,\n       165. , 165.5, 166. , 166.5, 167. , 167.5, 168. , 168.5, 169. , 169.5,\n       170. , 170.5, 171. , 171.5, 172. , 172.5, 173. , 173.5, 174. , 174.5,\n       175. , 175.5, 176. , 176.5, 177. , 177.5, 178. , 178.5, 179. , 179.5,\n       180. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6ce925a1-66dc-4c76-b2ef-575d94501fb8' class='xr-section-summary-in' type='checkbox'  ><label for='section-6ce925a1-66dc-4c76-b2ef-575d94501fb8' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2f7b1783-6741-4e17-9821-68d8d07347cc' class='xr-index-data-in' type='checkbox'/><label for='index-2f7b1783-6741-4e17-9821-68d8d07347cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2014-07-01 00:00:00&#x27;, &#x27;2014-07-01 06:00:00&#x27;,\n               &#x27;2014-07-01 12:00:00&#x27;, &#x27;2014-07-01 18:00:00&#x27;,\n               &#x27;2014-07-02 00:00:00&#x27;, &#x27;2014-07-02 06:00:00&#x27;,\n               &#x27;2014-07-02 12:00:00&#x27;, &#x27;2014-07-02 18:00:00&#x27;,\n               &#x27;2014-07-03 00:00:00&#x27;, &#x27;2014-07-03 06:00:00&#x27;,\n               ...\n               &#x27;2014-07-29 12:00:00&#x27;, &#x27;2014-07-29 18:00:00&#x27;,\n               &#x27;2014-07-30 00:00:00&#x27;, &#x27;2014-07-30 06:00:00&#x27;,\n               &#x27;2014-07-30 12:00:00&#x27;, &#x27;2014-07-30 18:00:00&#x27;,\n               &#x27;2014-07-31 00:00:00&#x27;, &#x27;2014-07-31 06:00:00&#x27;,\n               &#x27;2014-07-31 12:00:00&#x27;, &#x27;2014-07-31 18:00:00&#x27;],\n              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=124, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-29625449-ad2e-43b0-8432-9bea8b7a3dec' class='xr-index-data-in' type='checkbox'/><label for='index-29625449-ad2e-43b0-8432-9bea8b7a3dec' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([92500.0, 85000.0, 70000.0, 60000.0, 50000.0, 25000.0, 5000.0], dtype=&#x27;float64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-051c227d-3518-487a-be34-7edeacf3a6f6' class='xr-index-data-in' type='checkbox'/><label for='index-051c227d-3518-487a-be34-7edeacf3a6f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0,  0.5,  1.0,  1.5,  2.0,  2.5,  3.0,  3.5,  4.0,  4.5,\n       ...\n       55.5, 56.0, 56.5, 57.0, 57.5, 58.0, 58.5, 59.0, 59.5, 60.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9314d591-2960-492c-b875-75721d21b1cc' class='xr-index-data-in' type='checkbox'/><label for='index-9314d591-2960-492c-b875-75721d21b1cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100.0, 100.5, 101.0, 101.5, 102.0, 102.5, 103.0, 103.5, 104.0, 104.5,\n       ...\n       175.5, 176.0, 176.5, 177.0, 177.5, 178.0, 178.5, 179.0, 179.5, 180.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=161))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f7b6af23-ccee-4a16-8c4d-5241bfab5784' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f7b6af23-ccee-4a16-8c4d-5241bfab5784' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>northward_wind</dd><dt><span>long_name :</span></dt><dd>Northward Wind</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>original_name :</span></dt><dd>v</dd><dt><span>original_units :</span></dt><dd>m*s-1</dd><dt><span>history :</span></dt><dd>2017-09-01T06:58:04Z altered by CMOR: Converted units from &#x27;m*s-1&#x27; to &#x27;m s-1&#x27;. 2017-09-01T06:58:04Z altered by CMOR: replaced missing value flag (9.96921e+36) with standard missing value (1e+20). 2017-09-01T06:58:04Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div></li></ul></div></div>"},"metadata":{},"execution_count":14}],"execution_count":14},{"cell_type":"code","metadata":{"id":"985357FC699D4C24AACDB9EB97ABE124","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 40],crs=ccrs.PlateCarree())\nax.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels=False                               \ngl.right_labels=False\n    \nq = ax.quiver(lon, lat, \n              np.array(ua.sel(time='2014-7-23 12:00',plev=85000)), \n              np.array(va.sel(time='2014-7-23 12:00',plev=85000)),\n              regrid_shape=30, width=0.002, scale=300,\n              transform=ccrs.PlateCarree())\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('850 hPa',loc='left',fontsize=15)\nplt.title(str(ua.sel(time='2014-7-23 12:00').time.values)[0:16],loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 1 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/985357FC699D4C24AACDB9EB97ABE124/six1copsfd.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":15},{"cell_type":"code","metadata":{"id":"30C29F28BB9B4EC5B68FF8EBE5BA6675","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 计算风速\nwspd = mpcalc.wind_speed(ua, va)\nwspd","outputs":[{"output_type":"execute_result","data":{"text/plain":"<xarray.DataArray (time: 124, plev: 7, lat: 121, lon: 161)> Size: 68MB\n<Quantity([[[[ 1.3022264   1.248835    5.943801   ...  5.530365    5.332667\n     5.234038  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6.9689856  ... 14.665079   14.634084\n    14.439738  ]\n   [ 5.4089956   6.428735    6.5820346  ... 15.436344   15.365245\n    15.239414  ]\n   [ 5.3570566   6.4377947   6.106884   ... 16.171633   16.338684\n    16.459082  ]\n   ...\n   [ 6.024213    5.7046094   5.4072833  ...  2.4143445   2.2919786\n     2.1327596 ]\n   [ 6.183188    5.9649887   5.791523   ...  2.3349028   2.219912\n     2.093745  ]\n   [ 6.35644     6.277365    6.238218   ...  2.206543    2.1328702\n     2.0790584 ]]]], 'meter / second')>\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0","text/html":"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n<defs>\n<symbol id=\"icon-database\" viewBox=\"0 0 32 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4;\n}\n\n.xr-index-preview {\n  grid-column: 2 / 5;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-name,\n.xr-var-dims,\n.xr-var-dtype,\n.xr-preview,\n.xr-attrs dt {\n  white-space: nowrap;\n  overflow: hidden;\n  text-overflow: ellipsis;\n  padding-right: 10px;\n}\n\n.xr-var-name:hover,\n.xr-var-dims:hover,\n.xr-var-dtype:hover,\n.xr-attrs dt:hover {\n  overflow: visible;\n  width: auto;\n  z-index: 1;\n}\n\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  display: none;\n  background-color: var(--xr-background-color) !important;\n  padding-bottom: 5px !important;\n}\n\n.xr-var-attrs-in:checked ~ .xr-var-attrs,\n.xr-var-data-in:checked ~ .xr-var-data,\n.xr-index-data-in:checked ~ .xr-index-data {\n  display: block;\n}\n\n.xr-var-data > table {\n  float: right;\n}\n\n.xr-var-name span,\n.xr-var-data,\n.xr-index-name div,\n.xr-index-data,\n.xr-attrs {\n  padding-left: 25px !important;\n}\n\n.xr-attrs,\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  grid-column: 1 / -1;\n}\n\ndl.xr-attrs {\n  padding: 0;\n  margin: 0;\n  display: grid;\n  grid-template-columns: 125px auto;\n}\n\n.xr-attrs dt,\n.xr-attrs dd {\n  padding: 0;\n  margin: 0;\n  float: left;\n  padding-right: 10px;\n  width: auto;\n}\n\n.xr-attrs dt {\n  font-weight: normal;\n  grid-column: 1;\n}\n\n.xr-attrs dt:hover span {\n  display: inline-block;\n  background: var(--xr-background-color);\n  padding-right: 10px;\n}\n\n.xr-attrs dd {\n  grid-column: 2;\n  white-space: pre-wrap;\n  word-break: break-all;\n}\n\n.xr-icon-database,\n.xr-icon-file-text2,\n.xr-no-icon {\n  display: inline-block;\n  vertical-align: middle;\n  width: 1em;\n  height: 1.5em !important;\n  stroke-width: 0;\n  stroke: currentColor;\n  fill: currentColor;\n}\n</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 124, plev: 7, lat: 121, lon: 161)&gt; Size: 68MB\n&lt;Quantity([[[[ 1.3022264   1.248835    5.943801   ...  5.530365    5.332667\n     5.234038  ]\n   [ 0.7992342   2.0584426   8.501437   ...  5.158567    5.223607\n     5.2980967 ]\n   [ 1.246309    3.8280737   9.063484   ...  4.7236395   4.6885014\n     4.7298646 ]\n   ...\n   [ 5.7523184   5.52123     5.172321   ...  1.187582    1.0780067\n     1.3060287 ]\n   [ 3.3301053   3.5739923   3.8100324  ...  1.54147     0.7552995\n     0.8662426 ]\n   [ 2.6456475   2.642826    2.6175284  ...  3.92669     3.177028\n     2.824884  ]]\n\n  [[ 2.378189    1.8809075   2.7754817  ...  6.711699    6.8488727\n     6.979134  ]\n   [ 2.1941476   1.8551124   3.4699264  ...  6.256525    6.7218094\n     6.9876184 ]\n   [ 0.95758486  1.5859413   4.4672103  ...  5.619528    6.3457375\n     6.676497  ]\n...\n   [16.622036   16.378258   16.109547   ... 12.678336   12.2141285\n    11.930177  ]\n   [17.077486   16.883612   16.734882   ... 12.00194    11.597473\n    11.00846   ]\n   [16.989374   16.762083   16.55872    ... 11.539599   10.680423\n     9.555235  ]]\n\n  [[ 5.7629757   6.5307307   6.9689856  ... 14.665079   14.634084\n    14.439738  ]\n   [ 5.4089956   6.428735    6.5820346  ... 15.436344   15.365245\n    15.239414  ]\n   [ 5.3570566   6.4377947   6.106884   ... 16.171633   16.338684\n    16.459082  ]\n   ...\n   [ 6.024213    5.7046094   5.4072833  ...  2.4143445   2.2919786\n     2.1327596 ]\n   [ 6.183188    5.9649887   5.791523   ...  2.3349028   2.219912\n     2.093745  ]\n   [ 6.35644     6.277365    6.238218   ...  2.206543    2.1328702\n     2.0790584 ]]]], &#x27;meter / second&#x27;)&gt;\nCoordinates:\n  * time     (time) datetime64[ns] 992B 2014-07-01 ... 2014-07-31T18:00:00\n  * plev     (plev) float64 56B 9.25e+04 8.5e+04 7e+04 6e+04 5e+04 2.5e+04 5e+03\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 124</li><li><span class='xr-has-index'>plev</span>: 7</li><li><span class='xr-has-index'>lat</span>: 121</li><li><span class='xr-has-index'>lon</span>: 161</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2d7f200f-92d8-48eb-9136-797646def00a' class='xr-array-in' type='checkbox' checked><label for='section-2d7f200f-92d8-48eb-9136-797646def00a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>&lt;Quantity([[[[ 1.3022264   1.248835    5.943801   ...  5.530365    ...</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[[1.3022264242172241 1.2488349676132202 5.943800926208496 ...<br>    5.530364990234375 5.332666873931885 5.23403787612915]<br>   [0.7992342114448547 2.0584425926208496 8.501437187194824 ...<br>    5.158566951751709 5.223607063293457 5.298096656799316]<br>   [1.2463090419769287 3.828073740005493 9.063484191894531 ...<br>    4.723639488220215 4.688501358032227 4.729864597320557]<br>   ...<br>   [5.752318382263184 5.521230220794678 5.17232084274292 ...<br>    1.187582015991211 1.0780067443847656 1.3060287237167358]<br>   [3.3301053047180176 3.5739922523498535 3.810032367706299 ...<br>    1.5414700508117676 0.7552995085716248 0.8662425875663757]<br>   [2.6456475257873535 2.6428260803222656 2.6175284385681152 ...<br>    3.926690101623535 3.177027940750122 2.8248839378356934]]<br><br>  [[2.3781890869140625 1.8809075355529785 2.775481700897217 ...<br>    6.71169900894165 6.848872661590576 6.9791340827941895]<br>   [2.1941475868225098 1.8551124334335327 3.469926357269287 ...<br>    6.256525039672852 6.721809387207031 6.987618446350098]<br>   [0.9575848579406738 1.5859413146972656 4.467210292816162 ...<br>    5.619527816772461 6.345737457275391 6.676496982574463]<br>   ...<br>   [6.843843936920166 6.8765716552734375 6.599891662597656 ...<br>    0.4569343328475952 0.7148880362510681 1.5754719972610474]<br>   [6.229905128479004 5.928622722625732 5.574154853820801 ...<br>    1.684517741203308 1.8493846654891968 2.2207300662994385]<br>   [3.7410964965820312 2.987398147583008 2.4661290645599365 ...<br>    3.483199119567871 2.8092598915100098 2.792869806289673]]<br><br>  [[9.213691711425781 9.208746910095215 8.979597091674805 ...<br>    9.425893783569336 8.976295471191406 8.827964782714844]<br>   [10.083910942077637 10.252540588378906 9.804619789123535 ...<br>    9.40530776977539 8.95486831665039 8.661900520324707]<br>   [11.471576690673828 10.81949234008789 10.013206481933594 ...<br>    9.030835151672363 8.790846824645996 8.725340843200684]<br>   ...<br>   [5.595168113708496 5.639617443084717 5.720105171203613 ...<br>    2.644212245941162 1.956714391708374 2.2502710819244385]<br>   [4.443489074707031 4.8744215965271 5.321057319641113 ...<br>    3.5311620235443115 2.7540299892425537 2.069153308868408]<br>   [3.600271463394165 4.017831325531006 4.609912872314453 ...<br>    5.442671775817871 4.345090866088867 3.2820239067077637]]<br><br>  ...<br><br>  [[12.93340015411377 12.948466300964355 13.127245903015137 ...<br>    9.660530090332031 9.838411331176758 10.201583862304688]<br>   [12.178004264831543 12.154292106628418 12.803889274597168 ...<br>    9.466021537780762 9.204883575439453 9.122672080993652]<br>   [10.897323608398438 11.326022148132324 12.349567413330078 ...<br>    10.268885612487793 10.172325134277344 9.611592292785645]<br>   ...<br>   [2.1752753257751465 2.7933268547058105 3.990015983581543 ...<br>    10.845293045043945 10.018072128295898 9.431995391845703]<br>   [1.6937752962112427 1.866992473602295 2.315333843231201 ...<br>    10.486881256103516 9.787209510803223 9.021736145019531]<br>   [1.9052741527557373 2.143221855163574 2.45709228515625 ...<br>    10.407220840454102 9.834705352783203 9.2879056930542]]<br><br>  [[15.267570495605469 14.685088157653809 14.606781959533691 ...<br>    4.621564865112305 4.106480121612549 3.892399787902832]<br>   [14.977051734924316 14.726079940795898 14.096494674682617 ...<br>    4.857270240783691 4.659820556640625 5.258799076080322]<br>   [15.372396469116211 15.328900337219238 14.431102752685547 ...<br>    5.096523761749268 5.774832248687744 7.210753440856934]<br>   ...<br>   [8.883541107177734 9.351505279541016 10.40627384185791 ...<br>    36.344120025634766 37.45069122314453 38.58437728881836]<br>   [8.789952278137207 9.558453559875488 10.829607009887695 ...<br>    35.83713150024414 36.87541580200195 37.98497772216797]<br>   [9.084944725036621 9.998041152954102 11.315975189208984 ...<br>    35.509979248046875 36.38192367553711 37.38594055175781]]<br><br>  [[6.542664051055908 7.429566860198975 8.025654792785645 ...<br>    12.098165512084961 11.92564582824707 11.876587867736816]<br>   [7.254945755004883 7.646510601043701 8.439268112182617 ...<br>    11.994621276855469 11.631204605102539 11.469002723693848]<br>   [8.376343727111816 8.391176223754883 9.133057594299316 ...<br>    11.870233535766602 11.447578430175781 11.226601600646973]<br>   ...<br>   [2.3044610023498535 2.2592859268188477 2.275210380554199 ...<br>    2.6074438095092773 2.751807689666748 2.8376591205596924]<br>   [2.9971485137939453 2.973867654800415 2.870990514755249 ...<br>    2.5747599601745605 2.772400140762329 2.8951327800750732]<br>   [3.2556116580963135 3.359668016433716 3.2700977325439453 ...<br>    2.483752965927124 2.672243595123291 2.7996089458465576]]]<br><br><br> [[[2.2138478755950928 1.4019814729690552 1.722488522529602 ...<br>    5.063436508178711 4.727219581604004 4.518491744995117]<br>   [1.624394178390503 0.9598274230957031 2.7144393920898438 ...<br>    4.479555130004883 4.118669033050537 3.8511741161346436]<br>   [1.288453221321106 1.0589393377304077 4.331520080566406 ...<br>    4.072503566741943 3.8076999187469482 3.4214048385620117]<br>   ...<br>   [4.644990921020508 4.3397135734558105 4.124190330505371 ...<br>    0.8184300661087036 0.8268908858299255 1.8987559080123901]<br>   [4.102908611297607 3.7003588676452637 3.464110851287842 ...<br>    2.451197862625122 1.7274951934814453 0.7941890358924866]<br>   [3.003861904144287 2.7448532581329346 2.665130853652954 ...<br>    4.995248794555664 3.787932872772217 2.886096239089966]]<br><br>  [[2.4326767921447754 2.870121955871582 2.97822642326355 ...<br>    6.027248382568359 6.185144424438477 6.260499477386475]<br>   [2.9366676807403564 4.253746509552002 4.169104099273682 ...<br>    5.627115726470947 5.647929668426514 5.584787368774414]<br>   [3.247345209121704 3.4424033164978027 3.852285861968994 ...<br>    5.223464012145996 5.010459899902344 5.024145126342773]<br>   ...<br>   [4.882040977478027 4.524510860443115 4.279685974121094 ...<br>    2.8524343967437744 2.4419267177581787 2.65869140625]<br>   [4.21537446975708 3.8790535926818848 3.750155448913574 ...<br>    2.9225409030914307 2.5296242237091064 2.027634859085083]<br>   [3.052687644958496 2.8509039878845215 2.742780923843384 ...<br>    4.188558578491211 3.5824105739593506 3.151379346847534]]<br><br>  [[10.62936782836914 10.374592781066895 9.775444984436035 ...<br>    7.0492777824401855 7.245427131652832 7.722144603729248]<br>   [11.41243839263916 10.903088569641113 10.209787368774414 ...<br>    6.618521213531494 6.693906307220459 7.2817912101745605]<br>   [12.495575904846191 11.740966796875 11.095272064208984 ...<br>    6.708915710449219 6.523205280303955 6.744969367980957]<br>   ...<br>   [3.8640193939208984 4.221539497375488 4.98068380355835 ...<br>    6.157122611999512 5.779768466949463 5.040565490722656]<br>   [3.9448893070220947 4.654116153717041 5.339181900024414 ...<br>    5.5268707275390625 5.490084171295166 4.932552814483643]<br>   [4.6031951904296875 5.057920455932617 5.382485866546631 ...<br>    4.788173675537109 4.8629984855651855 4.769168853759766]]<br><br>  ...<br><br>  [[11.762389183044434 11.489495277404785 12.210552215576172 ...<br>    8.02959156036377 8.442707061767578 9.013957023620605]<br>   [10.316686630249023 10.695319175720215 11.822287559509277 ...<br>    8.237456321716309 8.300840377807617 8.438066482543945]<br>   [9.511162757873535 10.132601737976074 11.06886100769043 ...<br>    8.051170349121094 7.9762444496154785 8.298008918762207]<br>   ...<br>   [2.4597067832946777 4.279563903808594 6.4737701416015625 ...<br>    14.325200080871582 14.064987182617188 14.073785781860352]<br>   [2.4175796508789062 3.057941436767578 4.9962544441223145 ...<br>    14.318435668945312 14.011186599731445 13.787797927856445]<br>   [3.2477285861968994 3.228647232055664 4.441938877105713 ...<br>    13.893430709838867 13.627049446105957 13.443608283996582]]<br><br>  [[13.951770782470703 13.00369644165039 13.353575706481934 ...<br>    3.909430503845215 4.409618377685547 4.124618053436279]<br>   [14.267276763916016 12.870111465454102 11.235106468200684 ...<br>    5.439138412475586 5.773643493652344 6.077764987945557]<br>   [14.262185096740723 13.470274925231934 11.119978904724121 ...<br>    5.560862064361572 5.423022270202637 4.506792068481445]<br>   ...<br>   [13.902668952941895 14.18869686126709 13.921598434448242 ...<br>    23.100263595581055 23.88977813720703 24.859399795532227]<br>   [14.035317420959473 14.206610679626465 13.927968978881836 ...<br>    22.229930877685547 23.045961380004883 24.119888305664062]<br>   [14.521122932434082 14.907809257507324 14.838345527648926 ...<br>    22.9705753326416 23.75148582458496 24.76206398010254]]<br><br>  [[3.526207685470581 4.2433061599731445 4.9080963134765625 ...<br>    9.342625617980957 9.598177909851074 9.692200660705566]<br>   [4.557944297790527 4.954632759094238 5.612212657928467 ...<br>    9.757882118225098 10.134058952331543 10.340579986572266]<br>   [5.719414710998535 5.599314212799072 5.922703742980957 ...<br>    10.052114486694336 10.489066123962402 10.68554973602295]<br>   ...<br>   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6.4969377517700195 6.567088603973389 ...<br>    6.538337707519531 6.714389801025391 6.941501140594482]]<br><br>  ...<br><br>  [[8.360027313232422 7.963107109069824 7.134788513183594 ...<br>    7.664515018463135 8.118820190429688 8.5621919631958]<br>   [8.234825134277344 8.157708168029785 6.944149971008301 ...<br>    7.89781379699707 7.994434356689453 8.420049667358398]<br>   [7.7576494216918945 7.344354152679443 7.186388969421387 ...<br>    8.62889289855957 8.319113731384277 8.307483673095703]<br>   ...<br>   [9.654810905456543 9.31960391998291 9.153766632080078 ...<br>    3.9858338832855225 4.471677780151367 4.62169075012207]<br>   [11.37038803100586 10.859419822692871 10.436931610107422 ...<br>    3.8394041061401367 4.2992448806762695 4.233989238739014]<br>   [12.47398853302002 12.234644889831543 11.983146667480469 ...<br>    3.910604476928711 4.24041748046875 3.9930636882781982]]<br><br>  [[6.8544769287109375 6.43077278137207 5.510223865509033 ...<br>    2.3957810401916504 1.6666498184204102 1.4650508165359497]<br>   [3.9485998153686523 4.036410808563232 4.04486083984375 ...<br>    3.1285271644592285 2.8146138191223145 3.0475080013275146]<br>   [3.5498690605163574 4.325247764587402 2.893179416656494 ...<br>    4.336180686950684 4.177378177642822 4.463972568511963]<br>   ...<br>   [16.62203598022461 16.378257751464844 16.109546661376953 ...<br>    12.678336143493652 12.214128494262695 11.930176734924316]<br>   [17.077486038208008 16.88361167907715 16.734882354736328 ...<br>    12.00193977355957 11.59747314453125 11.00846004486084]<br>   [16.9893741607666 16.762083053588867 16.558719635009766 ...<br>    11.539599418640137 10.68042278289795 9.555234909057617]]<br><br>  [[5.762975692749023 6.530730724334717 6.968985557556152 ...<br>    14.665079116821289 14.63408374786377 14.439738273620605]<br>   [5.408995628356934 6.42873477935791 6.582034587860107 ...<br>    15.436344146728516 15.36524486541748 15.23941421508789]<br>   [5.357056617736816 6.4377946853637695 6.106884002685547 ...<br>    16.171632766723633 16.33868408203125 16.459081649780273]<br>   ...<br>   [6.024212837219238 5.704609394073486 5.407283306121826 ...<br>    2.414344549179077 2.291978597640991 2.1327595710754395]<br>   [6.183187961578369 5.964988708496094 5.791522979736328 ...<br>    2.334902763366699 2.219912052154541 2.093744993209839]<br>   [6.35644006729126 6.277365207672119 6.238217830657959 ...<br>    2.20654296875 2.1328701972961426 2.0790584087371826]]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>meter/second</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-c35be65a-16ca-45a2-b24c-65e815c8be13' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c35be65a-16ca-45a2-b24c-65e815c8be13' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2014-07-01 ... 2014-07-31T18:00:00</div><input id='attrs-676a23cb-e8e4-43a7-82eb-6d03dfd355a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-676a23cb-e8e4-43a7-82eb-6d03dfd355a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dcd2d4f-1bd2-4461-acec-0b9e9ba92059' class='xr-var-data-in' type='checkbox'><label for='data-1dcd2d4f-1bd2-4461-acec-0b9e9ba92059' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2014-07-01T00:00:00.000000000&#x27;, &#x27;2014-07-01T06:00:00.000000000&#x27;,\n       &#x27;2014-07-01T12:00:00.000000000&#x27;, &#x27;2014-07-01T18:00:00.000000000&#x27;,\n       &#x27;2014-07-02T00:00:00.000000000&#x27;, &#x27;2014-07-02T06:00:00.000000000&#x27;,\n       &#x27;2014-07-02T12:00:00.000000000&#x27;, &#x27;2014-07-02T18:00:00.000000000&#x27;,\n       &#x27;2014-07-03T00:00:00.000000000&#x27;, &#x27;2014-07-03T06:00:00.000000000&#x27;,\n       &#x27;2014-07-03T12:00:00.000000000&#x27;, &#x27;2014-07-03T18:00:00.000000000&#x27;,\n       &#x27;2014-07-04T00:00:00.000000000&#x27;, &#x27;2014-07-04T06:00:00.000000000&#x27;,\n       &#x27;2014-07-04T12:00:00.000000000&#x27;, &#x27;2014-07-04T18:00:00.000000000&#x27;,\n       &#x27;2014-07-05T00:00:00.000000000&#x27;, &#x27;2014-07-05T06:00:00.000000000&#x27;,\n       &#x27;2014-07-05T12:00:00.000000000&#x27;, &#x27;2014-07-05T18:00:00.000000000&#x27;,\n       &#x27;2014-07-06T00:00:00.000000000&#x27;, &#x27;2014-07-06T06:00:00.000000000&#x27;,\n       &#x27;2014-07-06T12:00:00.000000000&#x27;, &#x27;2014-07-06T18:00:00.000000000&#x27;,\n       &#x27;2014-07-07T00:00:00.000000000&#x27;, &#x27;2014-07-07T06:00:00.000000000&#x27;,\n       &#x27;2014-07-07T12:00:00.000000000&#x27;, &#x27;2014-07-07T18:00:00.000000000&#x27;,\n       &#x27;2014-07-08T00:00:00.000000000&#x27;, &#x27;2014-07-08T06:00:00.000000000&#x27;,\n       &#x27;2014-07-08T12:00:00.000000000&#x27;, &#x27;2014-07-08T18:00:00.000000000&#x27;,\n       &#x27;2014-07-09T00:00:00.000000000&#x27;, &#x27;2014-07-09T06:00:00.000000000&#x27;,\n       &#x27;2014-07-09T12:00:00.000000000&#x27;, &#x27;2014-07-09T18:00:00.000000000&#x27;,\n       &#x27;2014-07-10T00:00:00.000000000&#x27;, &#x27;2014-07-10T06:00:00.000000000&#x27;,\n       &#x27;2014-07-10T12:00:00.000000000&#x27;, &#x27;2014-07-10T18:00:00.000000000&#x27;,\n       &#x27;2014-07-11T00:00:00.000000000&#x27;, &#x27;2014-07-11T06:00:00.000000000&#x27;,\n       &#x27;2014-07-11T12:00:00.000000000&#x27;, &#x27;2014-07-11T18:00:00.000000000&#x27;,\n       &#x27;2014-07-12T00:00:00.000000000&#x27;, &#x27;2014-07-12T06:00:00.000000000&#x27;,\n       &#x27;2014-07-12T12:00:00.000000000&#x27;, &#x27;2014-07-12T18:00:00.000000000&#x27;,\n       &#x27;2014-07-13T00:00:00.000000000&#x27;, &#x27;2014-07-13T06:00:00.000000000&#x27;,\n       &#x27;2014-07-13T12:00:00.000000000&#x27;, &#x27;2014-07-13T18:00:00.000000000&#x27;,\n       &#x27;2014-07-14T00:00:00.000000000&#x27;, &#x27;2014-07-14T06:00:00.000000000&#x27;,\n       &#x27;2014-07-14T12:00:00.000000000&#x27;, &#x27;2014-07-14T18:00:00.000000000&#x27;,\n       &#x27;2014-07-15T00:00:00.000000000&#x27;, &#x27;2014-07-15T06:00:00.000000000&#x27;,\n       &#x27;2014-07-15T12:00:00.000000000&#x27;, &#x27;2014-07-15T18:00:00.000000000&#x27;,\n       &#x27;2014-07-16T00:00:00.000000000&#x27;, &#x27;2014-07-16T06:00:00.000000000&#x27;,\n       &#x27;2014-07-16T12:00:00.000000000&#x27;, &#x27;2014-07-16T18:00:00.000000000&#x27;,\n       &#x27;2014-07-17T00:00:00.000000000&#x27;, &#x27;2014-07-17T06:00:00.000000000&#x27;,\n       &#x27;2014-07-17T12:00:00.000000000&#x27;, &#x27;2014-07-17T18:00:00.000000000&#x27;,\n       &#x27;2014-07-18T00:00:00.000000000&#x27;, &#x27;2014-07-18T06:00:00.000000000&#x27;,\n       &#x27;2014-07-18T12:00:00.000000000&#x27;, &#x27;2014-07-18T18:00:00.000000000&#x27;,\n       &#x27;2014-07-19T00:00:00.000000000&#x27;, &#x27;2014-07-19T06:00:00.000000000&#x27;,\n       &#x27;2014-07-19T12:00:00.000000000&#x27;, &#x27;2014-07-19T18:00:00.000000000&#x27;,\n       &#x27;2014-07-20T00:00:00.000000000&#x27;, &#x27;2014-07-20T06:00:00.000000000&#x27;,\n       &#x27;2014-07-20T12:00:00.000000000&#x27;, &#x27;2014-07-20T18:00:00.000000000&#x27;,\n       &#x27;2014-07-21T00:00:00.000000000&#x27;, &#x27;2014-07-21T06:00:00.000000000&#x27;,\n       &#x27;2014-07-21T12:00:00.000000000&#x27;, &#x27;2014-07-21T18:00:00.000000000&#x27;,\n       &#x27;2014-07-22T00:00:00.000000000&#x27;, &#x27;2014-07-22T06:00:00.000000000&#x27;,\n       &#x27;2014-07-22T12:00:00.000000000&#x27;, &#x27;2014-07-22T18:00:00.000000000&#x27;,\n       &#x27;2014-07-23T00:00:00.000000000&#x27;, &#x27;2014-07-23T06:00:00.000000000&#x27;,\n       &#x27;2014-07-23T12:00:00.000000000&#x27;, &#x27;2014-07-23T18:00:00.000000000&#x27;,\n       &#x27;2014-07-24T00:00:00.000000000&#x27;, &#x27;2014-07-24T06:00:00.000000000&#x27;,\n       &#x27;2014-07-24T12:00:00.000000000&#x27;, &#x27;2014-07-24T18:00:00.000000000&#x27;,\n       &#x27;2014-07-25T00:00:00.000000000&#x27;, &#x27;2014-07-25T06:00:00.000000000&#x27;,\n       &#x27;2014-07-25T12:00:00.000000000&#x27;, &#x27;2014-07-25T18:00:00.000000000&#x27;,\n       &#x27;2014-07-26T00:00:00.000000000&#x27;, &#x27;2014-07-26T06:00:00.000000000&#x27;,\n       &#x27;2014-07-26T12:00:00.000000000&#x27;, &#x27;2014-07-26T18:00:00.000000000&#x27;,\n       &#x27;2014-07-27T00:00:00.000000000&#x27;, &#x27;2014-07-27T06:00:00.000000000&#x27;,\n       &#x27;2014-07-27T12:00:00.000000000&#x27;, &#x27;2014-07-27T18:00:00.000000000&#x27;,\n       &#x27;2014-07-28T00:00:00.000000000&#x27;, &#x27;2014-07-28T06:00:00.000000000&#x27;,\n       &#x27;2014-07-28T12:00:00.000000000&#x27;, &#x27;2014-07-28T18:00:00.000000000&#x27;,\n       &#x27;2014-07-29T00:00:00.000000000&#x27;, &#x27;2014-07-29T06:00:00.000000000&#x27;,\n       &#x27;2014-07-29T12:00:00.000000000&#x27;, &#x27;2014-07-29T18:00:00.000000000&#x27;,\n       &#x27;2014-07-30T00:00:00.000000000&#x27;, &#x27;2014-07-30T06:00:00.000000000&#x27;,\n       &#x27;2014-07-30T12:00:00.000000000&#x27;, &#x27;2014-07-30T18:00:00.000000000&#x27;,\n       &#x27;2014-07-31T00:00:00.000000000&#x27;, &#x27;2014-07-31T06:00:00.000000000&#x27;,\n       &#x27;2014-07-31T12:00:00.000000000&#x27;, &#x27;2014-07-31T18:00:00.000000000&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.25e+04 8.5e+04 ... 2.5e+04 5e+03</div><input id='attrs-308e1fbb-e076-4efb-a4ff-fbf3e74d3372' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-308e1fbb-e076-4efb-a4ff-fbf3e74d3372' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5073a66f-08d6-4e1c-86bf-1cd347f6aaaa' class='xr-var-data-in' type='checkbox'><label for='data-5073a66f-08d6-4e1c-86bf-1cd347f6aaaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([92500., 85000., 70000., 60000., 50000., 25000.,  5000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.5 1.0 1.5 ... 59.0 59.5 60.0</div><input id='attrs-fed085a7-769e-4740-8940-832dbf4368af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fed085a7-769e-4740-8940-832dbf4368af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca206df6-f0c7-4197-874e-238f0a3aeddb' class='xr-var-data-in' type='checkbox'><label for='data-ca206df6-f0c7-4197-874e-238f0a3aeddb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,\n        6. ,  6.5,  7. ,  7.5,  8. ,  8.5,  9. ,  9.5, 10. , 10.5, 11. , 11.5,\n       12. , 12.5, 13. , 13.5, 14. , 14.5, 15. , 15.5, 16. , 16.5, 17. , 17.5,\n       18. , 18.5, 19. , 19.5, 20. , 20.5, 21. , 21.5, 22. , 22.5, 23. , 23.5,\n       24. , 24.5, 25. , 25.5, 26. , 26.5, 27. , 27.5, 28. , 28.5, 29. , 29.5,\n       30. , 30.5, 31. , 31.5, 32. , 32.5, 33. , 33.5, 34. , 34.5, 35. , 35.5,\n       36. , 36.5, 37. , 37.5, 38. , 38.5, 39. , 39.5, 40. , 40.5, 41. , 41.5,\n       42. , 42.5, 43. , 43.5, 44. , 44.5, 45. , 45.5, 46. , 46.5, 47. , 47.5,\n       48. , 48.5, 49. , 49.5, 50. , 50.5, 51. , 51.5, 52. , 52.5, 53. , 53.5,\n       54. , 54.5, 55. , 55.5, 56. , 56.5, 57. , 57.5, 58. , 58.5, 59. , 59.5,\n       60. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.5 101.0 ... 179.5 180.0</div><input id='attrs-6e4ac103-a42c-4298-a4c9-a590ac995e15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e4ac103-a42c-4298-a4c9-a590ac995e15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-442553f0-5d1b-497c-8b1a-a7c7a92a5dd4' class='xr-var-data-in' type='checkbox'><label for='data-442553f0-5d1b-497c-8b1a-a7c7a92a5dd4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.5, 101. , 101.5, 102. , 102.5, 103. , 103.5, 104. , 104.5,\n       105. , 105.5, 106. , 106.5, 107. , 107.5, 108. , 108.5, 109. , 109.5,\n       110. , 110.5, 111. , 111.5, 112. , 112.5, 113. , 113.5, 114. , 114.5,\n       115. , 115.5, 116. , 116.5, 117. , 117.5, 118. , 118.5, 119. , 119.5,\n       120. , 120.5, 121. , 121.5, 122. , 122.5, 123. , 123.5, 124. , 124.5,\n       125. , 125.5, 126. , 126.5, 127. , 127.5, 128. , 128.5, 129. , 129.5,\n       130. , 130.5, 131. , 131.5, 132. , 132.5, 133. , 133.5, 134. , 134.5,\n       135. , 135.5, 136. , 136.5, 137. , 137.5, 138. , 138.5, 139. , 139.5,\n       140. , 140.5, 141. , 141.5, 142. , 142.5, 143. , 143.5, 144. , 144.5,\n       145. , 145.5, 146. , 146.5, 147. , 147.5, 148. , 148.5, 149. , 149.5,\n       150. , 150.5, 151. , 151.5, 152. , 152.5, 153. , 153.5, 154. , 154.5,\n       155. , 155.5, 156. , 156.5, 157. , 157.5, 158. , 158.5, 159. , 159.5,\n       160. , 160.5, 161. , 161.5, 162. , 162.5, 163. , 163.5, 164. , 164.5,\n       165. , 165.5, 166. , 166.5, 167. , 167.5, 168. , 168.5, 169. , 169.5,\n       170. , 170.5, 171. , 171.5, 172. , 172.5, 173. , 173.5, 174. , 174.5,\n       175. , 175.5, 176. , 176.5, 177. , 177.5, 178. , 178.5, 179. , 179.5,\n       180. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ecfa1e1-5f76-4399-8821-de10146c1987' class='xr-section-summary-in' type='checkbox'  ><label for='section-5ecfa1e1-5f76-4399-8821-de10146c1987' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-93e2804d-0a46-4ce5-823b-f47b821e49d9' class='xr-index-data-in' type='checkbox'/><label for='index-93e2804d-0a46-4ce5-823b-f47b821e49d9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2014-07-01 00:00:00&#x27;, &#x27;2014-07-01 06:00:00&#x27;,\n               &#x27;2014-07-01 12:00:00&#x27;, &#x27;2014-07-01 18:00:00&#x27;,\n               &#x27;2014-07-02 00:00:00&#x27;, &#x27;2014-07-02 06:00:00&#x27;,\n               &#x27;2014-07-02 12:00:00&#x27;, &#x27;2014-07-02 18:00:00&#x27;,\n               &#x27;2014-07-03 00:00:00&#x27;, &#x27;2014-07-03 06:00:00&#x27;,\n               ...\n               &#x27;2014-07-29 12:00:00&#x27;, &#x27;2014-07-29 18:00:00&#x27;,\n               &#x27;2014-07-30 00:00:00&#x27;, &#x27;2014-07-30 06:00:00&#x27;,\n               &#x27;2014-07-30 12:00:00&#x27;, &#x27;2014-07-30 18:00:00&#x27;,\n               &#x27;2014-07-31 00:00:00&#x27;, &#x27;2014-07-31 06:00:00&#x27;,\n               &#x27;2014-07-31 12:00:00&#x27;, &#x27;2014-07-31 18:00:00&#x27;],\n              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=124, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e9d66f21-26a9-4c30-ac7c-1ad03ed70339' class='xr-index-data-in' type='checkbox'/><label for='index-e9d66f21-26a9-4c30-ac7c-1ad03ed70339' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([92500.0, 85000.0, 70000.0, 60000.0, 50000.0, 25000.0, 5000.0], dtype=&#x27;float64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c5979980-d519-4dd9-b23a-0d65212d2b96' class='xr-index-data-in' type='checkbox'/><label for='index-c5979980-d519-4dd9-b23a-0d65212d2b96' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0,  0.5,  1.0,  1.5,  2.0,  2.5,  3.0,  3.5,  4.0,  4.5,\n       ...\n       55.5, 56.0, 56.5, 57.0, 57.5, 58.0, 58.5, 59.0, 59.5, 60.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f801158a-dc5e-455c-bf71-cefbf68a55d7' class='xr-index-data-in' type='checkbox'/><label for='index-f801158a-dc5e-455c-bf71-cefbf68a55d7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100.0, 100.5, 101.0, 101.5, 102.0, 102.5, 103.0, 103.5, 104.0, 104.5,\n       ...\n       175.5, 176.0, 176.5, 177.0, 177.5, 178.0, 178.5, 179.0, 179.5, 180.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=161))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-858e0142-72aa-4b65-9389-46c38c4cfa81' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-858e0142-72aa-4b65-9389-46c38c4cfa81' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"},"metadata":{},"execution_count":16}],"execution_count":16},{"cell_type":"code","metadata":{"id":"A523F47A19BA482DB63A0DA5EAC3E8B5","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 50],crs=ccrs.PlateCarree())\nplt.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels=False                               \ngl.right_labels=False\n\nim = ax.contourf(lon, lat, wspd.sel(time='2014-7-23 12:00',plev=85000), \n                 np.arange(0,55,5),\n                 extend='both',\n                 cmap=cmaps.MPL_YlGnBu, \n                 transform=ccrs.PlateCarree())\n\ncb = fig.colorbar(im, \n                  ticks=np.arange(0,55,5), \n                  orientation='vertical', \n                  extend='both', shrink=0.6,\n                  fraction=0.03, pad=0.02) \ncb.set_label(label='Wind Speed (m/s)', size=15)\ncb.ax.tick_params(labelsize=15)\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('850 hPa',loc='left',fontsize=15)\nplt.title(str(wspd.sel(time='2014-7-23 12:00').time.values)[0:16],loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/A523F47A19BA482DB63A0DA5EAC3E8B5/six1d1shz3.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":17},{"cell_type":"code","metadata":{"id":"49A082416FB14E69A8955B7EB5CF3A18","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 如果选择热带气旋中心位置的风速，会发现风速并不大\nwspd.sel(time='2014-7-23 12:00',lon=128.5,lat=22.0,plev=85000).values","outputs":[{"output_type":"execute_result","data":{"text/plain":"array(26.336712, dtype=float32)"},"metadata":{},"execution_count":18}],"execution_count":18},{"cell_type":"code","metadata":{"id":"D9301B5A19BC40568E364538C40B162C","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 因此，可以扩大搜索范围，获取热带气旋近中心最大风速，则可得到完全一致的风速结果\nwspd.sel(time='2014-7-23 12:00',lon=slice(126.5,129.5),lat=slice(20,24),plev=85000).values.max()","outputs":[{"output_type":"execute_result","data":{"text/plain":"51.30455"},"metadata":{},"execution_count":19}],"execution_count":19},{"cell_type":"markdown","metadata":{"id":"00A03CC7F08449D6A8547D4797151FD2","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"### 绝对涡度"},{"cell_type":"code","metadata":{"id":"8CFA821CF479481AAA56C60A1C88085A","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 计算850hPa绝对涡度\nds = xr.open_dataset('/home/mw/input/typhoon/data/train/ua_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc')\nua = ds.ua * units('m/s') \nds = xr.open_dataset('/home/mw/input/typhoon/data/train/va_6hrPlevPt_ECMWF-IFS-HR_highresSST-present_r1i1p1f1_gr_201407010000-201407311800.nc')\nva = ds.va * units('m/s')\navor_850 = mpcalc.absolute_vorticity(ua.sel(time='2014-7-23 12:00',plev=85000), va.sel(time='2014-7-23 12:00',plev=85000))\navor_850","outputs":[{"output_type":"execute_result","data":{"text/plain":"<xarray.DataArray (lat: 121, lon: 161)> Size: 156kB\n<Quantity([[-1.83590271e-06  9.58707466e-08  1.29511569e-05 ... -5.20499241e-06\n  -6.77454940e-06  2.61941374e-06]\n [ 5.99118029e-05  2.85154763e-05  1.22267653e-06 ...  5.46908593e-06\n  -3.12651901e-06 -3.45073783e-06]\n [ 5.08908834e-05  1.97254529e-05 -9.48465971e-06 ...  9.06154914e-06\n   1.02817492e-06 -7.38342892e-06]\n ...\n [ 5.98597355e-05  6.46551882e-05  7.61221881e-05 ...  2.27114181e-04\n   2.30963825e-04  2.20572940e-04]\n [ 9.02516472e-05  7.75163020e-05  5.98941532e-05 ...  2.56009418e-04\n   2.37797146e-04  2.13260600e-04]\n [ 1.04388733e-04  9.67493770e-05  7.76908465e-05 ...  2.80680199e-04\n   2.43178043e-04  2.12161356e-04]], '1 / second')>\nCoordinates:\n    time     datetime64[ns] 8B 2014-07-23T12:00:00\n    plev     float64 8B 8.5e+04\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0","text/html":"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n<defs>\n<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 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none;\n}\n\n.xr-section-summary,\n.xr-section-inline-details {\n  padding-top: 4px;\n  padding-bottom: 4px;\n}\n\n.xr-section-inline-details {\n  grid-column: 2 / -1;\n}\n\n.xr-section-details {\n  display: none;\n  grid-column: 1 / -1;\n  margin-bottom: 5px;\n}\n\n.xr-section-summary-in:checked ~ .xr-section-details {\n  display: contents;\n}\n\n.xr-array-wrap {\n  grid-column: 1 / -1;\n  display: grid;\n  grid-template-columns: 20px auto;\n}\n\n.xr-array-wrap > label {\n  grid-column: 1;\n  vertical-align: top;\n}\n\n.xr-preview {\n  color: var(--xr-font-color3);\n}\n\n.xr-array-preview,\n.xr-array-data {\n  padding: 0 5px !important;\n  grid-column: 2;\n}\n\n.xr-array-data,\n.xr-array-in:checked ~ .xr-array-preview {\n  display: none;\n}\n\n.xr-array-in:checked ~ .xr-array-data,\n.xr-array-preview {\n  display: inline-block;\n}\n\n.xr-dim-list {\n  display: inline-block !important;\n  list-style: none;\n  padding: 0 !important;\n  margin: 0;\n}\n\n.xr-dim-list li {\n  display: inline-block;\n  padding: 0;\n  margin: 0;\n}\n\n.xr-dim-list:before {\n  content: '(';\n}\n\n.xr-dim-list:after {\n  content: ')';\n}\n\n.xr-dim-list li:not(:last-child):after {\n  content: ',';\n  padding-right: 5px;\n}\n\n.xr-has-index {\n  font-weight: bold;\n}\n\n.xr-var-list,\n.xr-var-item {\n  display: contents;\n}\n\n.xr-var-item > div,\n.xr-var-item label,\n.xr-var-item > .xr-var-name span {\n  background-color: var(--xr-background-color-row-even);\n  margin-bottom: 0;\n}\n\n.xr-var-item > .xr-var-name:hover span {\n  padding-right: 5px;\n}\n\n.xr-var-list > li:nth-child(odd) > div,\n.xr-var-list > li:nth-child(odd) > label,\n.xr-var-list > li:nth-child(odd) > .xr-var-name span {\n  background-color: var(--xr-background-color-row-odd);\n}\n\n.xr-var-name {\n  grid-column: 1;\n}\n\n.xr-var-dims {\n  grid-column: 2;\n}\n\n.xr-var-dtype {\n  grid-column: 3;\n  text-align: right;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-preview {\n  grid-column: 4;\n}\n\n.xr-index-preview {\n  grid-column: 2 / 5;\n  color: var(--xr-font-color2);\n}\n\n.xr-var-name,\n.xr-var-dims,\n.xr-var-dtype,\n.xr-preview,\n.xr-attrs dt {\n  white-space: nowrap;\n  overflow: hidden;\n  text-overflow: ellipsis;\n  padding-right: 10px;\n}\n\n.xr-var-name:hover,\n.xr-var-dims:hover,\n.xr-var-dtype:hover,\n.xr-attrs dt:hover {\n  overflow: visible;\n  width: auto;\n  z-index: 1;\n}\n\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  display: none;\n  background-color: var(--xr-background-color) !important;\n  padding-bottom: 5px !important;\n}\n\n.xr-var-attrs-in:checked ~ .xr-var-attrs,\n.xr-var-data-in:checked ~ .xr-var-data,\n.xr-index-data-in:checked ~ .xr-index-data {\n  display: block;\n}\n\n.xr-var-data > table {\n  float: right;\n}\n\n.xr-var-name span,\n.xr-var-data,\n.xr-index-name div,\n.xr-index-data,\n.xr-attrs {\n  padding-left: 25px !important;\n}\n\n.xr-attrs,\n.xr-var-attrs,\n.xr-var-data,\n.xr-index-data {\n  grid-column: 1 / -1;\n}\n\ndl.xr-attrs {\n  padding: 0;\n  margin: 0;\n  display: grid;\n  grid-template-columns: 125px auto;\n}\n\n.xr-attrs dt,\n.xr-attrs dd {\n  padding: 0;\n  margin: 0;\n  float: left;\n  padding-right: 10px;\n  width: auto;\n}\n\n.xr-attrs dt {\n  font-weight: normal;\n  grid-column: 1;\n}\n\n.xr-attrs dt:hover span {\n  display: inline-block;\n  background: var(--xr-background-color);\n  padding-right: 10px;\n}\n\n.xr-attrs dd {\n  grid-column: 2;\n  white-space: pre-wrap;\n  word-break: break-all;\n}\n\n.xr-icon-database,\n.xr-icon-file-text2,\n.xr-no-icon {\n  display: inline-block;\n  vertical-align: middle;\n  width: 1em;\n  height: 1.5em !important;\n  stroke-width: 0;\n  stroke: currentColor;\n  fill: currentColor;\n}\n</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 121, lon: 161)&gt; Size: 156kB\n&lt;Quantity([[-1.83590271e-06  9.58707466e-08  1.29511569e-05 ... -5.20499241e-06\n  -6.77454940e-06  2.61941374e-06]\n [ 5.99118029e-05  2.85154763e-05  1.22267653e-06 ...  5.46908593e-06\n  -3.12651901e-06 -3.45073783e-06]\n [ 5.08908834e-05  1.97254529e-05 -9.48465971e-06 ...  9.06154914e-06\n   1.02817492e-06 -7.38342892e-06]\n ...\n [ 5.98597355e-05  6.46551882e-05  7.61221881e-05 ...  2.27114181e-04\n   2.30963825e-04  2.20572940e-04]\n [ 9.02516472e-05  7.75163020e-05  5.98941532e-05 ...  2.56009418e-04\n   2.37797146e-04  2.13260600e-04]\n [ 1.04388733e-04  9.67493770e-05  7.76908465e-05 ...  2.80680199e-04\n   2.43178043e-04  2.12161356e-04]], &#x27;1 / second&#x27;)&gt;\nCoordinates:\n    time     datetime64[ns] 8B 2014-07-23T12:00:00\n    plev     float64 8B 8.5e+04\n  * lat      (lat) float64 968B 0.0 0.5 1.0 1.5 2.0 ... 58.0 58.5 59.0 59.5 60.0\n  * lon      (lon) float64 1kB 100.0 100.5 101.0 101.5 ... 179.0 179.5 180.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 121</li><li><span class='xr-has-index'>lon</span>: 161</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0296dfd9-7d06-47b0-b32e-ab4417173a2b' class='xr-array-in' type='checkbox' checked><label for='section-0296dfd9-7d06-47b0-b32e-ab4417173a2b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>&lt;Quantity([[-1.83590271e-06  9.58707466e-08  1.29511569e-05 ... -5....</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[-1.835902705284761e-06 9.587074659028093e-08 1.2951156942508328e-05 ...<br>  -5.204992409661261e-06 -6.774549398205886e-06 2.61941373922648e-06]<br> [5.991180290672876e-05 2.8515476280820332e-05 1.2226765278633096e-06 ...<br>  5.4690859325955456e-06 -3.12651901079401e-06 -3.4507378284057697e-06]<br> [5.089088335920089e-05 1.9725452890240306e-05 -9.484659708345922e-06 ...<br>  9.061549139433768e-06 1.0281749198296827e-06 -7.3834289204717976e-06]<br> ...<br> [5.985973551449977e-05 6.465518821956565e-05 7.612218806830185e-05 ...<br>  0.00022711418073045257 0.00023096382494853818 0.00022057294002239525]<br> [9.025164718124112e-05 7.751630201665727e-05 5.989415322206776e-05 ...<br>  0.00025600941845659584 0.0002377971461300547 0.0002132605998264602]<br> [0.00010438873331584661 9.67493769541211e-05 7.769084646045515e-05 ...<br>  0.000280680198901135 0.0002431780429342551 0.00021216135608003069]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>1/second</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-e9eca963-b7f3-42e4-a15b-9d0bdc7ac433' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e9eca963-b7f3-42e4-a15b-9d0bdc7ac433' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2014-07-23T12:00:00</div><input id='attrs-1ac7246f-77ff-49d2-bbc1-44a8287caa43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ac7246f-77ff-49d2-bbc1-44a8287caa43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9481412-d318-40bd-927a-c3bac65c22fd' class='xr-var-data-in' type='checkbox'><label for='data-c9481412-d318-40bd-927a-c3bac65c22fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_metpy_axis :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2014-07-23T12:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>plev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.5e+04</div><input id='attrs-4677ff25-fac5-4be5-897c-a344f09c85f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4677ff25-fac5-4be5-897c-a344f09c85f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6268b339-24ee-41f3-87e7-98333453029c' class='xr-var-data-in' type='checkbox'><label for='data-6268b339-24ee-41f3-87e7-98333453029c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd><dt><span>_metpy_axis :</span></dt><dd>vertical</dd></dl></div><div class='xr-var-data'><pre>array(85000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.5 1.0 1.5 ... 59.0 59.5 60.0</div><input id='attrs-177d44c0-641c-4e13-b891-e03797ab49a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-177d44c0-641c-4e13-b891-e03797ab49a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50a39a89-20ec-4c90-808e-48f0a17a2087' class='xr-var-data-in' type='checkbox'><label for='data-50a39a89-20ec-4c90-808e-48f0a17a2087' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>_metpy_axis :</span></dt><dd>y,latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,\n        6. ,  6.5,  7. ,  7.5,  8. ,  8.5,  9. ,  9.5, 10. , 10.5, 11. , 11.5,\n       12. , 12.5, 13. , 13.5, 14. , 14.5, 15. , 15.5, 16. , 16.5, 17. , 17.5,\n       18. , 18.5, 19. , 19.5, 20. , 20.5, 21. , 21.5, 22. , 22.5, 23. , 23.5,\n       24. , 24.5, 25. , 25.5, 26. , 26.5, 27. , 27.5, 28. , 28.5, 29. , 29.5,\n       30. , 30.5, 31. , 31.5, 32. , 32.5, 33. , 33.5, 34. , 34.5, 35. , 35.5,\n       36. , 36.5, 37. , 37.5, 38. , 38.5, 39. , 39.5, 40. , 40.5, 41. , 41.5,\n       42. , 42.5, 43. , 43.5, 44. , 44.5, 45. , 45.5, 46. , 46.5, 47. , 47.5,\n       48. , 48.5, 49. , 49.5, 50. , 50.5, 51. , 51.5, 52. , 52.5, 53. , 53.5,\n       54. , 54.5, 55. , 55.5, 56. , 56.5, 57. , 57.5, 58. , 58.5, 59. , 59.5,\n       60. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.5 101.0 ... 179.5 180.0</div><input id='attrs-2cdb4b4e-dce6-49c1-a76c-a85f272b4f3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cdb4b4e-dce6-49c1-a76c-a85f272b4f3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9d168b6-07fe-4855-9d54-d79936d887d2' class='xr-var-data-in' type='checkbox'><label for='data-d9d168b6-07fe-4855-9d54-d79936d887d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>_metpy_axis :</span></dt><dd>x,longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.5, 101. , 101.5, 102. , 102.5, 103. , 103.5, 104. , 104.5,\n       105. , 105.5, 106. , 106.5, 107. , 107.5, 108. , 108.5, 109. , 109.5,\n       110. , 110.5, 111. , 111.5, 112. , 112.5, 113. , 113.5, 114. , 114.5,\n       115. , 115.5, 116. , 116.5, 117. , 117.5, 118. , 118.5, 119. , 119.5,\n       120. , 120.5, 121. , 121.5, 122. , 122.5, 123. , 123.5, 124. , 124.5,\n       125. , 125.5, 126. , 126.5, 127. , 127.5, 128. , 128.5, 129. , 129.5,\n       130. , 130.5, 131. , 131.5, 132. , 132.5, 133. , 133.5, 134. , 134.5,\n       135. , 135.5, 136. , 136.5, 137. , 137.5, 138. , 138.5, 139. , 139.5,\n       140. , 140.5, 141. , 141.5, 142. , 142.5, 143. , 143.5, 144. , 144.5,\n       145. , 145.5, 146. , 146.5, 147. , 147.5, 148. , 148.5, 149. , 149.5,\n       150. , 150.5, 151. , 151.5, 152. , 152.5, 153. , 153.5, 154. , 154.5,\n       155. , 155.5, 156. , 156.5, 157. , 157.5, 158. , 158.5, 159. , 159.5,\n       160. , 160.5, 161. , 161.5, 162. , 162.5, 163. , 163.5, 164. , 164.5,\n       165. , 165.5, 166. , 166.5, 167. , 167.5, 168. , 168.5, 169. , 169.5,\n       170. , 170.5, 171. , 171.5, 172. , 172.5, 173. , 173.5, 174. , 174.5,\n       175. , 175.5, 176. , 176.5, 177. , 177.5, 178. , 178.5, 179. , 179.5,\n       180. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a4470d10-c732-4e47-ae43-cdcbc9702fa0' class='xr-section-summary-in' type='checkbox'  ><label for='section-a4470d10-c732-4e47-ae43-cdcbc9702fa0' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-35179285-b901-4956-9fcf-80bcf9d164a1' class='xr-index-data-in' type='checkbox'/><label for='index-35179285-b901-4956-9fcf-80bcf9d164a1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0,  0.5,  1.0,  1.5,  2.0,  2.5,  3.0,  3.5,  4.0,  4.5,\n       ...\n       55.5, 56.0, 56.5, 57.0, 57.5, 58.0, 58.5, 59.0, 59.5, 60.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-164555ab-74d2-43cc-b7bc-3451702faa97' class='xr-index-data-in' type='checkbox'/><label for='index-164555ab-74d2-43cc-b7bc-3451702faa97' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100.0, 100.5, 101.0, 101.5, 102.0, 102.5, 103.0, 103.5, 104.0, 104.5,\n       ...\n       175.5, 176.0, 176.5, 177.0, 177.5, 178.0, 178.5, 179.0, 179.5, 180.0],\n      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=161))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1455e9dc-eaef-49be-8045-4a379ebc5c09' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1455e9dc-eaef-49be-8045-4a379ebc5c09' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"},"metadata":{},"execution_count":20}],"execution_count":20},{"cell_type":"code","metadata":{"id":"D62E959017E24DD9BA57A60BD95424D9","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"fig = plt.figure(figsize=(10,8))\nax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=ccrs.PlateCarree())\nax.set_extent([100, 180, 0, 50],crs=ccrs.PlateCarree())\nplt.tick_params(labelsize=15)\ngl = ax.gridlines(draw_labels=True, linewidth=0.5, linestyle='--')\ngl.top_labels = False\ngl.right_labels = False\n\nim = ax.pcolormesh(lon, lat, avor_850 * 10**5, \n                   vmin=-20,vmax=20,\n                   cmap=cmaps.cmp_b2r, \n                   transform=ccrs.PlateCarree())\n\ncb = fig.colorbar(im, ticks=np.arange(-20,25,5), orientation='vertical', \n                  extend='both', shrink=0.6,\n                  fraction=0.03, pad=0.02) \ncb.set_label(label='absolute_vorticity (*$10^5$ $s^{-1}$)', size=15)\ncb.ax.tick_params(labelsize=15)\n\nplt.title('ECMWF-IFS-HR',fontsize=15)\nplt.title('850 hPa',loc='left',fontsize=15)\nplt.title('Time:2014-07',loc='right',fontsize=15)\nplt.show()","outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","text/html":"<img src=\"https://cdn.kesci.com/upload/rt/D62E959017E24DD9BA57A60BD95424D9/six1dhtmuo.png\">"},"metadata":{"needs_background":"light"}}],"execution_count":21},{"cell_type":"markdown","metadata":{"id":"F75C97692FE04D1B9A9DCC50B825B869","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"## 提交格式与评分说明  \n为便于评分，测试集中已给出**2014年8月和9月**的西北太平洋热带气旋的**出现时刻以及初始时刻的属性**，如下面表格所示："},{"cell_type":"code","metadata":{"id":"ECE335AFD7F24B2CA7D3B2A6179BA602","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 查看测试集\ndf = pd.read_csv('/home/mw/input/typhoon/data/test/test_tc_data.csv')\ndf","outputs":[{"output_type":"execute_result","data":{"text/plain":"      id  number             time    lon   lat      pres  wind\n0      1       1   2014/8/4 12:00  152.0  22.5  100286.0  18.0\n1      2       1   2014/8/4 18:00    NaN   NaN       NaN   NaN\n2      3       1    2014/8/5 0:00    NaN   NaN       NaN   NaN\n3      4       1    2014/8/5 6:00    NaN   NaN       NaN   NaN\n4      5       1   2014/8/5 12:00    NaN   NaN       NaN   NaN\n..   ...     ...              ...    ...   ...       ...   ...\n202  203       7  2014/9/29 18:00    NaN   NaN       NaN   NaN\n203  204       7   2014/9/30 0:00    NaN   NaN       NaN   NaN\n204  205       7   2014/9/30 6:00    NaN   NaN       NaN   NaN\n205  206       7  2014/9/30 12:00    NaN   NaN       NaN   NaN\n206  207       7  2014/9/30 18:00    NaN   NaN       NaN   NaN\n\n[207 rows x 7 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>number</th>\n      <th>time</th>\n      <th>lon</th>\n      <th>lat</th>\n      <th>pres</th>\n      <th>wind</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>1</td>\n      <td>2014/8/4 12:00</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>1</td>\n      <td>2014/8/4 18:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>1</td>\n      <td>2014/8/5 0:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>1</td>\n      <td>2014/8/5 6:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>1</td>\n      <td>2014/8/5 12:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>202</th>\n      <td>203</td>\n      <td>7</td>\n      <td>2014/9/29 18:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>203</th>\n      <td>204</td>\n      <td>7</td>\n      <td>2014/9/30 0:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>204</th>\n      <td>205</td>\n      <td>7</td>\n      <td>2014/9/30 6:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>205</th>\n      <td>206</td>\n      <td>7</td>\n      <td>2014/9/30 12:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>206</th>\n      <td>207</td>\n      <td>7</td>\n      <td>2014/9/30 18:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n<p>207 rows × 7 columns</p>\n</div>"},"metadata":{},"execution_count":22}],"execution_count":22},{"cell_type":"markdown","metadata":{"id":"6FC57EA4D62D4350B699A8E32E4609B8","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"每个热带气旋初始时刻之外的**地理位置、海平面最低气压和850hPa最大风速**需要建立检测算法进行补全。  \n\n**id列从1开始连续编号，number表示热带气旋编号（数字相同表示同一个热带气旋）**，可以通过如下方式进行填充："},{"cell_type":"code","metadata":{"id":"005D71562B604276BC4E4109C5B0AEB5","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 创建提交数据示例代码：逐行进行填充\ndf.loc[1,'lon'] = 152\ndf.loc[1,'lat'] = 22.5\ndf.loc[1,'pres'] = 100286\ndf.loc[1,'wind'] = 18\ndf","outputs":[{"output_type":"execute_result","data":{"text/plain":"      id  number             time    lon   lat      pres  wind\n0      1       1   2014/8/4 12:00  152.0  22.5  100286.0  18.0\n1      2       1   2014/8/4 18:00  152.0  22.5  100286.0  18.0\n2      3       1    2014/8/5 0:00    NaN   NaN       NaN   NaN\n3      4       1    2014/8/5 6:00    NaN   NaN       NaN   NaN\n4      5       1   2014/8/5 12:00    NaN   NaN       NaN   NaN\n..   ...     ...              ...    ...   ...       ...   ...\n202  203       7  2014/9/29 18:00    NaN   NaN       NaN   NaN\n203  204       7   2014/9/30 0:00    NaN   NaN       NaN   NaN\n204  205       7   2014/9/30 6:00    NaN   NaN       NaN   NaN\n205  206       7  2014/9/30 12:00    NaN   NaN       NaN   NaN\n206  207       7  2014/9/30 18:00    NaN   NaN       NaN   NaN\n\n[207 rows x 7 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>number</th>\n      <th>time</th>\n      <th>lon</th>\n      <th>lat</th>\n      <th>pres</th>\n      <th>wind</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>1</td>\n      <td>2014/8/4 12:00</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>1</td>\n      <td>2014/8/4 18:00</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>1</td>\n      <td>2014/8/5 0:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>1</td>\n      <td>2014/8/5 6:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>1</td>\n      <td>2014/8/5 12:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>202</th>\n      <td>203</td>\n      <td>7</td>\n      <td>2014/9/29 18:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>203</th>\n      <td>204</td>\n      <td>7</td>\n      <td>2014/9/30 0:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>204</th>\n      <td>205</td>\n      <td>7</td>\n      <td>2014/9/30 6:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>205</th>\n      <td>206</td>\n      <td>7</td>\n      <td>2014/9/30 12:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>206</th>\n      <td>207</td>\n      <td>7</td>\n      <td>2014/9/30 18:00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n<p>207 rows × 7 columns</p>\n</div>"},"metadata":{},"execution_count":23}],"execution_count":23},{"cell_type":"code","metadata":{"id":"5CAEA51D23844477BFCB99FDDB696D20","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 创建提交数据示例代码：批量进行填充\n# 注意：此处是批量赋值了初始时刻的属性，不代表真实的台风特征\ndata_all = []\nfor tc_num in range(1,8):\n    data = df[df['number']==tc_num].reset_index(drop=True)\n    for i in range(len(data)-1):\n        data.loc[i+1,['lon','lat','pres','wind']] = data.loc[0,['lon','lat','pres','wind']]\n    data_all.append(data)\ndata_all = pd.concat(data_all)\ndel data_all['number'], data_all['time']\ndata_all","outputs":[{"output_type":"execute_result","data":{"text/plain":"     id    lon   lat      pres  wind\n0     1  152.0  22.5  100286.0  18.0\n1     2  152.0  22.5  100286.0  18.0\n2     3  152.0  22.5  100286.0  18.0\n3     4  152.0  22.5  100286.0  18.0\n4     5  152.0  22.5  100286.0  18.0\n..  ...    ...   ...       ...   ...\n15  203  134.0  17.0   99869.0  18.0\n16  204  134.0  17.0   99869.0  18.0\n17  205  134.0  17.0   99869.0  18.0\n18  206  134.0  17.0   99869.0  18.0\n19  207  134.0  17.0   99869.0  18.0\n\n[207 rows x 5 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>lon</th>\n      <th>lat</th>\n      <th>pres</th>\n      <th>wind</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>152.0</td>\n      <td>22.5</td>\n      <td>100286.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>203</td>\n      <td>134.0</td>\n      <td>17.0</td>\n      <td>99869.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>204</td>\n      <td>134.0</td>\n      <td>17.0</td>\n      <td>99869.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>205</td>\n      <td>134.0</td>\n      <td>17.0</td>\n      <td>99869.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>206</td>\n      <td>134.0</td>\n      <td>17.0</td>\n      <td>99869.0</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>207</td>\n      <td>134.0</td>\n      <td>17.0</td>\n      <td>99869.0</td>\n      <td>18.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>207 rows × 5 columns</p>\n</div>"},"metadata":{},"execution_count":24}],"execution_count":24},{"cell_type":"code","metadata":{"id":"9FA7732D318542EA9813E1A9CD8E967D","notebookId":"66cec22aeb486dd4e9a64332","jupyter":{},"collapsed":false,"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 保存csv表格\ndata_all.to_csv('submit.csv',index=False)","outputs":[],"execution_count":25},{"cell_type":"markdown","metadata":{"id":"2EC81474DC1449BAB641BC76434C2FE2","notebookId":"66cec22aeb486dd4e9a64332","runtime":{"status":"default","execution_status":null,"is_visible":false},"jupyter":{},"scrolled":false,"tags":[],"slideshow":{"slide_type":"slide"}},"source":"模型的评分由以下3个部分组成：  \n**位置分：** 计算每个热带气旋轨迹的经度和纬度的均方根误差的平均值（占比60%）  \n**气压分：** 计算每个热带气旋轨迹的中心最低气压的均方根误差的平均值（占比20%）  \n**风速分：** 计算每个热带气旋轨迹的850hPa近中心最大风速的均方根误差的平均值（占比20%）  \n\n**score = 0.6 位置分 + 0.2 气压分 + 0.2 风速分**  \n\n格式：与训练集保持一致，经纬度保留一位小数，气压和风速四舍五入取整，时间间隔为6小时。  \n## 更多探索  \n1、本示例给出了模拟数据中热带气旋轨迹点的属性特征，主要包含**气压、风场、温度以及涡度**特征，以说明训练集数据的准确性。  \n\n2、根据气压、风场、温度以及涡度的空间分布可以确定热带气旋特征，台风检测算法可以**基于特征进行监督学习**，或者**建立约束条件进行非监督学习**。"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python","nbconvert_exporter":"python","file_extension":".py","version":"3.5.2","pygments_lexer":"ipython3"}},"nbformat":4,"nbformat_minor":0}